Comparison Method Research Articles

Controlling parameters proportional integral derivative of DC motor using a gradient-based optimizer

In this paper, a gradient-based optimizer (GBO) algorithm is presented to optimize the parameters of a proportional integral derivative (PID) controller in DC motor control. The GBO algorithm which mathematically models and mimics is inspired by the gradient-based Newton method. It was developed to address various optimization issues. To determine the performance of the proposed method, a comparison method with the ant colony optimization (ACO) method. It was compared using the integral of time multiplied absolute error (ITAE). They are most popularly used in the literature. From the test results, the proposed method is promising and has better effectiveness. The proposed method, namely GBO-PID, shows the best performance.

A skeleton-based method for exercise recognition based on 3D coordinates of human joints

<p>The aim of the work is to develop the method of identification and comparison of poses and exercises performed by a person that will have a low sensitivity to data errors. This method uses their formal descriptions in the form of conjunctions of logical statements and should work regardless of the shooting angle at which the video was taken and the proportions of the person on it. Each statement describes the position of the joints relative to each other along one of the axes. The joint coordinates are corrected by taking into account the length of the bones that connect them that eliminates the necessity to process outliers and it also improves the accuracy of joints positioning. Removal of errors out of the data using the method of averaging the graph along each axis at every step. In order to do this, consecutive points are grouped so that the difference between the maximum and the minimum does not exceed the error. The groups are then filtered to leave only those in which both are smaller or both are larger. The proposed method of identification requires just a modern smartphone and has no restrictions on how to take video of exercises.</p>

Метод определения эффективности вариантов организации перевозок барже-буксирными составами

A study has been conducted on the method of evaluating options for organizing cargo transportation by barge-tow trains based on determining their effectiveness. Using the methods of the classical theory of transport processes, this problem has no quantitative solution, since it is not possible to take into account the regrouping of the composition during the passage of the route. To overcome this problem, additional mathematical tools have been developed for constructing integral time and velocity matrices, an objective function and graphs of the ratios of the total volume of transported cargo to the time it was en route. The consistent implementation of the proposed tools ensures the coherence of the calculation methods for determining the effectiveness of a flight with and without regrouping on the route, and also makes it possible to select the most appropriate option for organizing transportation. The cumulative result allows us to reflect the method of evaluation, comparison and selection of the most effective option for organizing a flight / group of flights, taking into account the ability to set individual parameters for the movement of the train and cargo. An example of approximation of the coordinate points of the route from the Nizhne-Svirsky shipping lock to Lake Ladoga is illustrated, as well as an example of discretization of an inland waterway section according to a three-level model. The parameters of equalization of the objective function of determining the efficiency of cargo transportation are considered. It is concluded that the optimal transportation option can be carried out on the basis of a combined approach, when several parameters are taken into account or sequentially set in the process of modeling the operation of ships. Graphs have been built that demonstrate the differences between the ways of organizing flights.

Technical-technology aspect and financial analysis of sweet potato (Ipomoea batatas L) flour processing agroindustry in Lampung province

Lampung Province is one of the Sumatra archipelago's fifth sweet potato-producing provinces. To provide added value and encourage the growth of agro-industry in Lampung Province, the development of sweet potato flour processing is needed. This study aims to determine the business feasibility of sweet potato flour in Lampung Province from raw materials, technical technology, and financial aspects. The research involved agencies and related institutions in Lampung Province and Lampung Tengah Regency. The research method used was a survey and interview method. The data obtained were analyzed in stages using the Exponential Comparison Method (ECM) and business feasibility analysis. The finding showed that the SP flour agro-industry is feasible to be established with a capacity of 4 tons of fresh SP as raw material in Way Pengubuan, Lampung Tengah District, Lampung Province. The project needs an initial investment capital of 3.36 billion and an annual operational capital of 14.44 billion. The project is projected to yield an NPV value of IDR. 1,320,768,285 over a 10-year business projection period, with an IRR of 21%, Net B/C of 1.11, and a PBP of 4 years and 17 days.

Finite‐time pinning synchronization control for multi‐layer complex networks

AbstractThe synchronization of multi‐layer networks can greatly improve production and life efficiency, thus having important research significance. In this article, the finite‐time pinning synchronization control strategy is investigated for multi‐layer networks. A new finite‐time pinning controller, which not only considers the intra‐layer coupling connection, but also the inter‐layer coupling connection, is designed. The pinning synchronization criteria for the multi‐layer networks is established based on the finite‐time control protocols. Additionally, the corresponding convergence analysis are also provided. Finally, the effectiveness of the obtained theoretical results is illustrated using three comparison methods in a two‐layer network.

Long short-term memory (LSTM) neural networks for predicting dynamic responses and application in piezoelectric energy harvesting

Abstract Long Short-Time Memory (LSTM) deep neural networks are capable of learning order dependence in sequence problems and capturing long-term, non-linear temporal dependencies between the input and out of a system. With the long-term vision to model dynamical systems to which analytical or numerical methods are impossible or difficult to apply, this paper presents a study of modeling system dynamics and predicting responses using the LSTM networks, which have demonstrated excellent capability in predicting single-mode responses in a prior study. However, the LSTM network exhibits difficulties in modeling and predicting multi-mode responses accurately. To resolve the multi-mode issue, this paper presents an approach that obtains an equivalent network consisting of a set of sub-networks learned on isolated modes, and demonstrates its effectiveness on a simulated 2-degree-of-freedom (2DOF) mass-spring-damper system of nonlinear Duffing springs. The second part of the paper is focused on the application of the proposed approach in piezoelectric energy harvesting. Experiments are conducted on a harvester subjected to random base-motion excitation and exhibiting nonlinearity in its multi-mode response. Both the direct and mode-separation LSTM modeling approaches are applied to predict the output voltage given a random base-motion excitation. The mode-separation approach outperforms the direct approach significantly, and yields an excellent match between the actual and predicted responses. Specifically, for a test electrical voltage response of RMS value 0.2241 V, the difference between the actual test and predicted responses by using the mode-separation approach has an RMS value of 0.0504 V, compared to 0.1645 V obtained by using the direct LSTM approach. It is also much lower than the RMS value of 0.1835 V obtained by using the attention-based LSTM network, another comparison method. Leveraging a deep learning strategy, the validated approach opens up opportunities for accurately modeling energy harvesting systems of high complexities and/or strong nonlinearities.

#2485 CellMatchR—RNA-seq based matching of kidney cell lines to kidney reference cell types

Abstract Background and Aims Cultured kidney cell lines are broadly used to model the physiology and pathophysiology of the kidney. Due to immortalization, passaging and culture conditions, a cell line's gene expression profile might differ greatly from the primary cells it was originally derived from. This might be further enhanced by experimental treatments with compounds or genetic modifications. It is therefore a relevant question if a given cell culture system is still the appropriate model for a certain disease or scientific investigations. Reasoning that RNA sequencing (RNA-seq) based transcriptomes are generated as part of many experimental setups and hence may be used to address this question, we developed and tested an RNA-seq based approach, CellMatchR. This approach matches kidney cell lines, primary cells and even tissue specimen to known kidney reference cell types to determine which primary kidney cell type is the most similar and to what degree global gene expression or the expression of selected marker genes differs. Method CellMatchR uses published murine and human kidney single cell- and tubule-level transcriptomic datasets from healthy mice and human donors as references. Single cell datasets were further processed to pseudobulk references for each of the contained cell types. Then RNA-seq data from cell lines or tissues of interest (test data) was compared to the reference (pseudo)bulk data with Spearman correlations of gene counts-per-million values (CPM) or Euclidean distance using log-transformed CPM values. Both approaches were systematically tested for various combinations of test and reference datasets across different species and using global gene expression (i.e. all genes measured in reference and test datasets) and a set of 315 manually curated, kidney cell type marker genes. Results We sequentially used different kidney tissue types, primary cells and cell lines as positive controls and matched them to our reference datasets. Spearman correlations of gene expression rankings showed the highest correlation coefficients with biologically correct reference cell types (examples in Fig. 1A-C). We found Spearman correlations to be superior to Euclidean distances as method of comparison. Analyses based on global gene expression compared to our curated set of 315 kidney cell type marker genes yielded similar results. Notably, correlation coefficients were higher and showed less variation between reference cell types when using the global gene set. Matchings across species, i.e. using murine test and human reference data or vice versa still yielded mostly correct results. However, correlation coefficients were generally lower (i.e. rho = 0.9 vs. 0.6) and varied more across reference datasets if comparisons were performed across species. Using published RNA-seq data for different cell lines of the proximal tubule (e.g. human HK-2 and opossum OKH cells) we observed low similarities with proximal tubule cells (Fig. 1D), whereas two tested cell lines of the collecting duct (mIMCD-3 and mpkCCD cells) plausibly showed the highest similarity to medullary cell types like collecting duct and Loop of Henle cells. The most similar reference cell types did not change in mIMCD-3 cells when kept in 2-dimensional vs. 3-dimensional culture conditions, and in mpkCCD cells when the osmolality of the culture medium was changed from 300 to 600 mosmol/kg. Also, a Pkd1 knockout in mIMCD-3 cells did not change the most similar reference cell type in our analyses (Fig. 1E and F). Conclusion Our CellMatchR approach uses publicly available kidney single cell and bulk RNA-seq datasets and combines these with simple, computationally fast yet effective statistical methods to determine similarities of kidney cell lines and tissue samples to reference cell types of interest. It can easily be implemented by trained users or integrated into online resources for usage with a visual interface. It relies on RNA-seq data from the cell lines of interest and hence presents a feasible complementary method to check the general similarity of cell culture models to kidney cell types and assess their stability across experimental conditions.

Bridge crack segmentation and measurement based on SOLOv2 segmentation model

With the continuous increase of vehicular traffic, the safety caused by bridge crack damage is becoming increasingly prominent. Bridge crack analysis and measurement are of great significance for promoting road traffic safety. However, existing bridge crack image segmentation methods have shortcomings in processing image detail features, resulting in the inability to better measure the actual size of bridge cracks. Therefore, to further optimize the calculation method, a bridge crack image segmentation method based on improved SOLOv2 is designed to achieve more accurate bridge image segmentation. Based on the image segmentation results and combined with the skeleton data extraction method, a bridge crack calculation method is designed. From the results, the segmentation accuracy for crack images was 92.05 % and 93.57 %, respectively. The average mIoU of AM-SOLOv2 method was 0.75, significantly lower than commonly used crack image segmentation methods. In addition, the mIoU value variation amplitude of the AM-SOLOv2 method was relatively smaller. The crack length and width errors were within 0.05 mm and 0.06 mm, significantly lower than the comparison method. It indicates that this method can achieve more accurate crack image segmentation and calculation. This is beneficial for a deeper understanding of the performance degradation and crack damage evolution of bridge structures, thereby improving bridge design and construction technology.

Основные подходы в информационном обеспечении проектов на получение государственной поддержки компаниями несырьевого сектора

The relevance of the chosen topic is justified by the need to research and develop measures aimed at reducing the negative impact of the unpredictable environment of the Russian economy in the face of overcoming economic sanctions. One of such measures of state support could be an information system for participants in foreign economic activity, taking into account the main approaches in information support of projects funded from the federal budget. The development of the system is based on marketing research of participants in foreign economic activity. As part of the development of measures of state support, market research includes expert assessment, methods of comparison and grouping, index method, and matrix algebra, i.e., it is based on methods of comprehensive analysis of economic activities. The tools under consideration allow forecasting practical results of project evaluation and analysis receiving state support. In conclusion, by integrating theoretical insights with practical methodologies, stakeholders can navigate complex economic environments and capitalize on emerging opportunities. Moving forward, continued research and innovation in information support systems will be essential for promoting sustainable development and resilience in the face of economic challenges.

Quantitative study on the color of traditional dwellings in Jianxi River Basin, Fujian Province, based on the lab color space model

ABSTRACT The color palette of traditional dwellings is intricately shaped by the characteristics of the geographical environment and the long-standing lifestyle of residents, thus constituting a vital component of rural culture. However, the rapid development in recent years has resulted in the dilapidation of rural features, including haphazard colors employed in buildings. With the advancement of science and technology, the studies of color have transitioned from a qualitative to a quantitative approach. Through a comprehensive comparison of RGB, HSB, CMYK, and Lab color spaces, as well as an evaluation of color card comparison method, software analysis method, and instrument measurement method; this paper reveals that employing the instrument measurement method in conjunction with the Lab color space enables independent assessment free from subjective influence. This approach facilitates more objective and accurate collection of color data while ensuring seamless and lossless transmission between devices. Therefore, to safeguard and enhance the authenticity of traditional dwellings and preserve the architectural style of traditional villages, this paper focuses on investigating the color palette of traditional dwellings in the Jianxi River Basin. The CM-700d spectrophotometer is employed for color data collection, while quantitative analysis is conducted using the Lab color space to unravel the color logics in this region. The findings reveal that earth yellow (average Lab (50.35,7.40,19.63)) constitutes the main color of rammed earth walls, complemented by dark brown (average Lab (38.72,2.97,8.58)) tiled roofs and gray-brown (average Lab (41.95,4.30,12.75)) stone wall bases as accent color; additionally, gray-yellow (average Lab (49 .82,1 .93,10.98)) brick gatehouses serve as accent colors. The integration between these colors and nature is harmonious; however, the absence of distinct color layers and highlights in the traditional dwellings necessitates incorporating bright architectural decorations along with arrangements of flowering plants. This paper conducted a quantitative analysis on the color of traditional dwellings with three main objectives. Firstly, to establish a comprehensive color database that can effectively preserve and promote regional traditional dwelling colors, while aiding designers in capturing regional color characteristics. Secondly, by collecting precise color data, this paper lays the groundwork for future applications of digital color technology. Lastly, it aims to explore the regional color logic and its potential integration with future studies on color evaluation to uncover preferred color combinations among the public for dwellings.

УДОСКОНАЛЕННЯ КОНЦЕПТУАЛЬНИХ ЗАСАД ЄВРОІНТЕГРАЦІЇ ТА ФІНАНСОВО-ПРАВОВІ МЕХАНІЗМИ ПРИСКОРЕННЯ ВСТУПУ УКРАЇНИ В ЄС

Introduction. Since 2022, Ukraine has been following the path of “classical accession” to the EU, which involves the compliance with the Copenhagen criteria and adoption of the common EU legislation (acquis) in 33 policy areas/ chapters. But advancement withing this scenario is a long and resource-intensive process. Problem Statement. The urgent task is to find an optimal model of joining the EU with coherence to a reasonable time frame of this course, achieving high results of European integration and identification of the sources of funding for carrying out reforms and overcoming the consequences of the war after reducing the potential of the Ukraine Facility. Purpose - identification of the current financial and legal problems of the European integration process for Ukraine, generalization of the methodological pillars of the concept of staged accession to the EU as a more progressive version over the classic accession model, design of the policy proposals for updating monitoring tools and financial incentives for progressing across the subsequent stages towards the EU membership. Methods. General scientific and special methods are applied: reviews of theoretical sources, advisory and research papers, analysis of statistical data and legal documents, historical method, logical method, methods of comparison and synthesis. Results. The article summarizes the methodological pillars of the concept of staged accession to the EU, systematizes the legal mechanisms of negotiations and obtaining EU membership, shows the financial aspects of the European integration process, including access to the EU cohesion funds, and elaborates practically important proposals for the activity of the EU institutions and national bodies as to the operationalization of the model of staged accession. Conclusions. The staged accession model is the most holistic and logically structured concept that can evolve a predictable progress towards the EU membership. The model should be based on the European Commission's quantitative assessments of countries' preparedness for the membership within the framework of negotiating clusters and chapters. A system of performance indicators is also required that will record progress of the candidate countries across stages and will set the ground for disbursements from the EU funds in line with specified ratios. Since 2028, the new EU medium-term fiscal framework should provide for the formation of new funds to finance the recovery of Ukraine's economy and the application of the EU's cohesion policy towards Ukraine.

The influence of sports games on the formation of technical skills of athletes in ukrainian belt wrestling

The article reveals current issues of forming the high level of technical fitness of athletes in Ukrainian belt wrestling. The main task of a technical training of an athlete is the formation of skills and abilities to perform competitive actions that allow to effectively use the athlete's capabilities in the process of sports activity. Technical skills training in any sport is aimed at teaching an athlete the technique of movements, improving them to perfection. The purpose of the research: to determine the influence of sports games on the formation of the level of technical skills of athletes in Ukrainian belt wrestling at the stage of preparation for major competitions. Research methods: analysis and synthesis of literary sources, methods of observation and comparison, pedagogical research methods (testing of physical qualities: coordination, speed and strength, power abilities, flexibility), medical and biological research methods, methods of mathematical statistics. Conclusions: the level of athletes' technical skills in the experimental group during the period of the pedagogical experiment by the indicator - throws of the partner, the speed of throws increased by 21.8% in relation to the control group - 4.7%.

Enhanced differential evolution-Rao optimization with distance comparison method and its application in optimal sizing of truss structures

A new decision-making approach based on distance measures is established in this study to effectively reduce unnecessary structural analyses in performing truss optimization by metaheuristic algorithms. This approach termed distance comparison (DiC) judges a new design candidate as worth evaluating by using its distance from the best solution. The new candidate solution will be omitted without evaluating it if it is not closer to the best solution than the one being compared. The DiC method is integrated with a novel hybrid metaheuristic based on differential evolution (DE) and the Rao algorithm. In the proposed hybrid strategy, a modified Rao algorithm and an enhanced DE are applied adaptively based on the population diversity to utilize the advantage of each one for a specific stage of the optimization process. Six truss sizing examples with continuous variables, including the 10-bar and 200-bar planar trusses and the 25-bar, 72-bar, 120-bar, and 942-bar spatial trusses, are examined to evaluate the effectiveness of the proposed method. Numerical results demonstrate that DiC significantly reduces the number of structural analyses. Moreover, the performance of the proposed hybrid metaheuristic algorithm conducted on the examples is better than that of some state-of-the-art metaheuristic algorithms.

The Influence of Spatial Heterogeneity of Urban Green Space on Surface Temperature

Urban green space (UGS) has been recognized as a key factor in enhancing the urban ecosystem balance, particularly in arid areas. It is often considered an effective means to mitigate the urban heat island (UHI) effect. In this study, the reference comparison method was utilized to optimize the process of nighttime lighting data; the random forest classification method was employed to extract UGS data; and the radiative transfer method was applied in land surface temperature (LST) inversion. Additionally, moving window analysis was conducted to assess the robustness of the results. The objective of this research was to analyze the spatial distribution characteristics of UGS and LST and to explore their bivariate local spatial autocorrelations by calculating four landscape metrics, including the aggregation index (AI), edge density (ED), patch density (PD), and area-weighted mean shape index (Shape_am). It was found that the distribution of UGS in the study area was uneven, with higher temperatures in the eastern and western regions and lower temperatures in the central and southern regions. The results also revealed that ED, PD, and Shape_am were negatively correlated with LST, with correlation coefficients being −0.469, −0.388, and −0.411, respectively, indicating that UGS in these regions were more effective in terms of cooling effect. Conversely, AI was found to be positively correlated with LST (Moran’ I index of 0.449), indicating that surface temperatures were relatively higher in regions of high aggregation. In essence, the fragmented, complex, and evenly distributed green patches in the study area provided a better cooling effect. These findings should persuade decision makers and municipal planners to allocate more UGS in cities for UHI alleviation to improve quality of life and enhance recreational opportunities.

Adaptation of the Russian accounting system for non-financial assets in accordance with the International Public Sector Accounting Standards: A problem analysis. Part 2

Subject. This article analyzes the areas of concern of accounting for non-financial assets in State-funded (municipal) and autonomous institutions in accordance with the International Public Sector Accounting Standards. Objectives. The article aims to identify and analyze the areas of concern associated with the adaptation of the Russian system of accounting for non-financial assets in accordance with the International Public Sector Accounting Standards based on a comparison of the main provisions of the International Financial Reporting Standards and the Russian Federal Accounting Standards for the public sector. Methods. For the study, I used the methods of comparison, systematization, and data generalization. Results. The article systematizes the main theoretical approaches to the study of issues in the field of adaptation of the Russian system of accounting for non-financial assets in accordance with the International Public Sector Accounting Standards. Relevance. The results of the study and the theories of adaptation of the Russian system of accounting for non-financial assets in accordance with the International Public Sector Accounting Standards can be used for the theoretical study of this issue, as well as in practical activities in State-owned (municipal) publicly-funded and autonomous institutions.

A data collection system model for sustainability reporting

Subject. This article explores the relationship between accounting analytics data and sustainability reporting indicators, and analyzes the importance of using accounting analytics data for sustainability reporting. Objectives. The article aims to identify the role of accounting in the process of sustainability reporting. Methods. For the study, I used the methods of analysis, comparison and generalization. Results. The article presents an original model of a data collection system for the formation of sustainability reporting. Conclusions. Effective use of the data collection system model for sustainability reporting can help companies obtain detailed information about their impact on the economy, society and the environment, which contributes to more informed sustainability management.

Air Traffic Flow Prediction with Spatiotemporal Knowledge Distillation Network

Accurate air traffic flow prediction assists controllers formulate control strategies in advance and alleviate air traffic congestion, which is important to flight safety. While existing works have made significant efforts in exploring the high dynamics and heterogeneous interactions of historical air traffic flow, two key challenges still remain. (1) The transfer patterns of air traffic are intricate, subject to numerous constraints and limitations such as controllers, flight regulations, and other regulatory factors. Relying solely on mining historical traffic evolution patterns makes it difficult to accurately predict the constrained air traffic flow. (2) Weather conditions exert a substantial influence on air traffic, making it exceptionally difficult to simulate the impact of external factors (such as thunderstorms) on the evolution of air traffic flow patterns. To address these two challenges, we propose a Spatiotemporal Knowledge Distillation Network (ST-KDN) for air traffic flow prediction. Firstly, recognizing the inherent future insights embedded within flight plans, we develop a “teacher-student” distillation model. This model leverages the prior knowledge of upstream-downstream migration patterns and future air traffic trends inherent in flight plans. Subsequently, to model the influence of external factors and predict air traffic flow disturbed by thunderstorm weather, we propose a student network based on the “parallel-fusion” structure. Finally, employing a feature-based knowledge distillation approach to integrate prior knowledge from flight plans and extract meteorological features, our method can accurately capture complex and constrained spatiotemporal dependencies in air traffic and explicitly model the impact of weather on air traffic flow. Experimental results on real-world flight data demonstrate that our method can achieve better prediction performance than other state-of-the-art comparison methods, and the advantages of the proposed method are particularly prominent in modeling the complicated transfer pattern of air traffic and inferring nonrecurrent flow patterns.

Liver Resection vs Nonsurgical Treatments for Patients With Early Multinodular Hepatocellular Carcinoma

The 2022 Barcelona Clinic Liver Cancer algorithm currently discourages liver resection (LR) for patients with multinodular hepatocellular carcinoma (HCC) presenting with 2 or 3 nodules that are each 3 cm or smaller. To compare the efficacy of liver resection (LR), percutaneous radiofrequency ablation (PRFA), and transarterial chemoembolization (TACE) in patients with multinodular HCC. This cohort study is a retrospective analysis conducted using data from the HE.RC.O.LE.S register (n = 5331) for LR patients and the ITA.LI.CA database (n = 7056) for PRFA and TACE patients. A matching-adjusted indirect comparison (MAIC) method was applied to balance data and potential confounding factors between the 3 groups. Included were patients from multiple centers from 2008 to 2020; data were analyzed from January to December 2023. LR, PRFA, or TACE. Survival rates at 1, 3, and 5 years were calculated. Cox MAIC-weighted multivariable analysis and competing risk analysis were used to assess outcomes. A total of 720 patients with early multinodular HCC were included, 543 males (75.4%), 177 females (24.6%), and 350 individuals older than 70 years (48.6%). There were 296 patients in the LR group, 240 who underwent PRFA, and 184 who underwent TACE. After MAIC, LR exhibited 1-, 3-, and 5-year survival rates of 89.11%, 70.98%, and 56.44%, respectively. PRFA showed rates of 94.01%, 65.20%, and 39.93%, while TACE displayed rates of 90.88%, 48.95%, and 29.24%. Multivariable Cox survival analysis in the weighted population showed a survival benefit over alternative treatments (PRFA vs LR: hazard ratio [HR], 1.41; 95% CI, 1.07-1.86; P = .01; TACE vs LR: HR, 1.86; 95% CI, 1.29-2.68; P = .001). Competing risk analysis confirmed a lower risk of cancer-related death in LR compared with PRFA and TACE. For patients with early multinodular HCC who are ineligible for transplant, LR should be prioritized as the primary therapeutic option, followed by PRFA and TACE when LR is not feasible. These findings provide valuable insights for clinical decision-making in this patient population.

High-precision comparison method of right dihedral angle using differential wavefront sensing

High-precision comparison method of right dihedral angle using differential wavefront sensing

Enamel Remineralisation with a Novel Sodium Fluoride-Infused Bristle Toothbrush.

This study aims to investigate whether toothbrushes with fluoride-infused bristles have any (re)mineralisation effects on bovine enamel. Bovine incisors (N = 160) were extracted, and the buccal side of the crown was cut into dimensions of ~5 mm × 5 mm with a low-speed saw. These specimens were randomly allocated into four groups: half (80 teeth) were stored in demineralising solution (DM), and the other half were stored in deionised water (DW) for 96 h. Then, they were brushed with a force of 2.0 ± 0.1 N for five min with a manual toothbrush with either fluoride-infused (TF) or regular (TR) bristles. Microhardness (Vickers), X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDS), and scanning electron microscopy (SEM) were used to investigate the surfaces of the bovine enamel specimens before and after brushing. Two-way ANOVA was used to analyse the hardness data, and the pairwise comparison method was used to analyse the Ca/P ratio, for each group at α = 0.05. The results show that brushing with either of these toothbrushes increased the Vickers microhardness on DM and DW enamel (p < 0.001), whereas hydroxyapatite was revealed in all groups by XRD. The DM samples showed a significant increase (p < 0.05) in the Ca/P ratios after brushing with TR and TF. Conversely, under DW conditions, these ratios decreased significantly after brushing. In terms of the F atomic%, TF increased significantly. SEM revealed mineral deposition in the DM groups after toothbrushing. To conclude, toothbrushing effectively induces the microhardness of sound and demineralised enamel, while fluoride-infused bristles might be able to retain fluoride on the enamel surface.