Method For Quantitative Analysis Research Articles

GT-CAM: Game Theory Based Class Activation Map for GCN.

Graph Convolutional Networks (GCN) have shown outstanding performance in skeleton-based behavior recognition. However, their opacity hampers further development. Researches on the explainability of deep learning have provided solutions to this issue, with Class Activation Map (CAM) algorithms being a class of explainable methods. However, existing CAM algorithms applies to GCN often independently compute the contribution of individual nodes, overlooking the interactions between nodes in the skeleton. Therefore, we propose a game theory based class activation map for GCN (GT-CAM). First, GT-CAM integrates Shapley values with gradient weights to calculate node importance, producing an activation map that highlights the critical role of nodes in decision-making. It also reveals the cooperative dynamics between nodes or local subgraphs for a more comprehensive explanation. Second, to reduce the computational burden of Shapley values, we propose a method for calculating Shapley values of node coalitions. Lastly, to evaluate the rationality of coalition partitioning, we propose a rationality evaluation method based on bipartite game interaction and cooperative game theory. Additionally, we introduce an efficient calculation method for the coalition rationality coefficient based on the Monte Carlo method. Experimental results demonstrate that GT-CAM outperforms other competitive interpretation methods in visualization and quantitative analysis.

Qualitative and Quantitative Analysis Method of Recombinant Collagen in Complex Matrix Based on HPLC-MS/MS

The purpose of this study is to achieve the quantitative detection of recombinant type III collagen (rh-COL-III) in dressings with complex matrix. First of all, the marker peptide (GEAGIPGVPGAK) of rhCOL-III was identified with HPLC-MS/MS. Then, a qualitative and quantitative method based on marker peptides was established and validated. In order to obtain higher sensitivity, a pretreatment method of liquid, gel, and ointment dressings was optimized. The reference material for quantification was combined using rhCOL-III and blank matrix of each dressing. The results indicated that the relative standard deviation (RSD) of the quantitative method was 2.77%, and the RSD of intraday and interday precision was 2.76% and 2.31%, respectively. The spiking recovery rate was between 80% and 90%. The optimal pretreatment method was Tris-HCl solvent replacement. The optimal trypsin concentration for the dressing solution was 20 μg in 500 μL. The method of preparing standard substances with a blank matrix can effectively eliminate the influence of the matrix effect on the quantitative results. The average spiking recovery rates of 50 μg/mL, 100 μg/mL, and 200 μg/mL in three different dressings ranged from 80% to 120%. The quantitative detection of limit (LOD) of rhCOL-III was 1 ng/mL, 2 ng/g, and 1 ng/g in liquid, ointment, and gel dressings.

THE INFLUENCE OF RETURN ON ASSETS, RETURN ON EQUITY, AND EARNINGS PER SHARE ON STOCK PRICES IN TECHNOLOGY SECTOR COMPANIES LISTED ON THE INDONESIA STOCK EXCHANGE (IDX)

Stock price is one of the important indicators of a company's success. The purpose of this study is to determine the influence of Return on Assets (ROA), Return on Equity (ROE), and Earnings Per Share (EPS) on stock prices. The data analysis method used in this study is quantitative analysis, which involves analyzing numerical data and using statistical calculations to test hypotheses. The quantitative data analysis methods applied in this research include descriptive statistics tests, classical assumption tests, and multiple linear regression analysis. Out of a population of 22 companies, a sample of 15 companies was selected for this study, covering the period from 2021 to 2023. The data analysis results indicate that Return on Assets (ROA) does not have a significant effect on stock prices, as indicated by t-value < t-table (0.824 < 2.018) with a significance of 0.415 > 0.05. Similarly, the analysis shows that Return on Equity (ROE) also does not significantly influence stock prices, with a t-value < t-table (-0.919 < 2.018) and a significance of 0.364 > 0.05. It can be concluded that neither ROA nor ROE significantly impacts stock prices. However, Earnings Per Share (EPS) does have a significant influence on stock prices, with a significance of 0.020. Future researchers are encouraged to conduct studies using different variables, such as ROA, ROE, and EPS, and to expand the sample size to achieve more in-depth research.

LC-MS/MS-Based Concurrent Quantification of Cannabidiol and Melatonin in Mouse Plasma to Elucidate Complex PK Interactions

LC-MS/MS-Based Concurrent Quantification of Cannabidiol and Melatonin in Mouse Plasma to Elucidate Complex PK Interactions

”Decolonization“ discourse in anti-russian telegram channels aimed at north Caucasus (a content analysis)

In recent years social media has turned out to be a new way of controlling minds of people and forming the way they view the world. North Caucasus has always been a complex multi-ethnic and multi-religious region. Territorial disputes and old (but not forgotten) conflicts make North Caucasus easy to try manipulating to stir it away from Russia. The idea of ”decolonization“ of Russia has resurfaced again after the Special military operation. The article presents an analysis of Telegram channels which are connected by anti-Russian rhetoric, promote “decolonization” and are focused on North Caucasus. The social graph method is used to create visual representation of the network of channels and connections between them. The quantitative content analysis method was used to analyze the text. We were able to identify five main thematic categories: “Special military operation in Ukraine”, “Islam”, “pan-Caucasian identity”, “history”, “genocide of the peoples of the North Caucasus”. The main purpose of these publications is to create a negative image of Russia, as well as to create an image of the oppressed North Caucasus colonized peoples. The level of influence of these posts on the real population of the region is the main question. We suggest that there are several information spaces: internal regional (news channels and local bloggers) and external (all the anti-Russian channels). It will be possible to talk about their merger only in two cases: if permanent connections emerge between them or if the thematic content of publications becomes sufficiently similar.

Application of improved matrix dilution method in quantitative analysis of Ni-Co-Mn ternary precursor

Abstract When using energy-dispersive X-ray fluorescence (EDXRF) to analyze Ni-Co-Mn (NCM) samples, if the standard sample's concentration greatly differs from the unknown sample's concentration, the traditional matrix dilution method requires repeated dilution and measurement. This makes the process time-consuming and labor-intensive. This study proposes an improved matrix dilution method to reduce sample preparation and analysis. This method first establishes a functional relationship model between the dilution factor and the characteristic X-ray intensity. Then the characteristic X-ray intensity of the analyzed element can be calculated by this model, avoiding unnecessary dilution and measurement steps. To verify the effectiveness of this method, the dilution factors and characteristic X-ray intensities of the test samples were fitted using the established functional relationship. The fitting results showed that the fitting coefficients of determination of the Mn, Co, and Ni were all 0.999. Quantitative analysis was performed on the characteristic X-ray intensity fitting values and measured values of the test samples. The results showed that the quantitative results of the two were consistent. The average error of the three elements for both methods was 1.1% and 0.7%, respectively. It shows that through the established functional relationship, the characteristic X-ray intensity can be effectively calculated by the dilution factor. This method can be applied to samples with identical elements and proportions of target elements, but with different concentrations, using the same set of standard samples.

Features of the methodology for assessing the innovative activity of industrial enterprises in the context of digitalization

This article is devoted to the author’s methodology for assessing the innovative activity of an enterprise aimed at integrating quantitative and qualitative indicators. This technique will allow you to more accurately reflect the level of innovation activity, identify the main factors affecting the effectiveness of innovation implementation, as well as form a strategy for further development. The paper considers the key elements of the proposed methodology. The results of the study can be applied in the practice of industrial enterprise management. The methodology can be used by state statistical agencies to monitor and evaluate the innovative activities of industrial enterprises. The implementation of this methodology can contribute to a deeper understanding of the processes associated with innovation and support informed management decisions. The methodological base of the study includes methods of quantitative and qualitative analysis, statistical analysis, factor analysis, and methods of expert assessments.

Preservation of the Author’s Tonality as a Tool for Evaluating Translation Quality

Introduction. This paper examines the methodology of text analysis using phono-semantic assessment based on the “VAAL-mini” program. The study includes an analysis of the original text and its translation to identify the author's tonality and its [non]preservation in the translation. The relevance of the chosen topic is determined by the application of psycholinguistic methods in the interpretation of V.P. Belyanin and the use of quantitative text analysis methods. The novelty of the research lies in employing the domestic linguistic computer program “VAAL-mini” as a tool capable of categorizing emotional elements of the text. Methodology and sources. The methodological foundation of the research is a psycholinguistic approach to assessing the quality of translation, which justifies the significance of the author category in the interpretation and translation of fiction texts. It also allows for an examination of how translation affects the perception and emotional response of the reader, as well as how accurately the translator conveys the cognitive and emotional aspects of the original text. The primary research method proposed is a quantitative method using the computer program “VAAL-mini”, which is capable of categorizing the emotional elements of the text. The material for the study is the novel by P. Suskind “Perfume: The Story of a Murderer” and its translation into Russian by E.V. Vengerova. Results and discussion. The literature review conducted allows for tracing the current state of psycholinguistics as per Belyanin and its developmental dynamics. In accordance with the identified concept, we performed a comprehensive analysis of P. Suskind's work “Perfume: The Story of a Murderer” and its Russian translation. The results of this analysis help to gain a deeper understanding of the emotional and lexical components of the text, as well as to assess the quality of the translation. The integration of a psycholinguistic approach with modern quantitative analysis methods-using corresponding computer programs enables a more comprehensive understanding of the studied work. Conclusion. As a result of the analysis based on determining the type of text using the linguistic application VAAL-mini, findings were obtained that refuted the external (qualitative) impression of stylistic and emotional equivalence between Süskind's original text and E.V. Vengerova's translation of the novel. This result demonstrates the viability of the proposed methodology for assessing translation quality.

Unveiling the Impact of Emotional Regulation on Academic Procrastination

This study examines how consumer perceptions of the Skintific brand, product quality, and pricing influence product selections among 110 FBHIS students at Muhammadiyah University of Sidoarjo. Using online questionnaires and quantitative analysis methods, including validity and reliability tests, multiple linear regression, and t-tests, the research reveals significant relationships between brand image, product quality, pricing, and consumer purchasing decisions. The findings emphasize the importance of these factors in shaping consumer behavior, particularly among university students, and offer insights for skincare companies targeting this demographic to enhance brand image, maintain product quality, and offer competitive pricing strategies. Highlight: Quantitative Analysis: Validity, reliability tests, regression for consumer behavior research. University Sample: Investigated FBHIS students' purchasing choices at Sidoarjo University. Strong Associations: Brand image, product quality, pricing linked to consumer decisions. Keywoard: Consumer perceptions, Skintific brand, Product quality, Pricing, Decisions

Stations of the Publicum Portorium Illyrici are a Strong Predictor of the Mithraic Presence in the Danubian Provinces: Geographical Analysis of the Distribution of the Roman Cult of Mithras

Abstract The article examines the relationship between the Roman cult of Mithras and members of the publicum portorium Illyrici, the Roman customs office active in the Danubian provinces, who have been discussed in previous research as potentially important carriers of this cult. To investigate this relationship and its extent, spatial proximity analysis is performed with respect to documented portorium stations and confirmed Mithraic finds. For comparative purposes, the spatial proximity between portorium stations and finds relating to other selected Graeco-Roman deities was also examined. On the basis of the results of this analysis, it is possible to conclude that Mithraic finds are located significantly closer to customs stations than those of other Graeco-Roman deities (with the exception of Jupiter, the main Graeco-Roman god) and that the presence of a portorium station strongly predicts the presence of a Mithraic cult at a given site or in its immediate vicinity, especially in the Western cluster of portorium provinces. Thus, in a nuanced form and using a quantitative method of geographical analysis, the study supports previous conclusions about the importance of portorium officials as a social group significantly involved in the spread of the Roman cult of Mithras in the Danubian provinces.

Application of Natural Science Methods in Social Science Research

The introduction of natural science methodologies into social science research aims to enhance the scientific rigor and validity of studies through precise techniques. By employing quantitative analysis, data mining, and model construction, researchers are able to delve deeper into the complexities of social phenomena, injecting new vitality into traditional qualitative research. Quantitative analysis methods render research outcomes more objective and reproducible, while data mining techniques can extract underlying patterns and trends from vast amounts of data. Model construction offers a systematic understanding of social dynamic processes, supporting the prediction and intervention of future social developments. Computer simulation technologies, particularly with the backing of big data and high-performance computing, enable hypothesis testing and virtual experiments on social systems, allowing for multi-level and multi-perspective observations of social phenomena. This interdisciplinary integration not only provides new research tools and methodologies for the social sciences but also effectively fosters the interchange of knowledge between different disciplines. However, continuous reflection and adjustment in practical applications are necessary to address the potential pitfalls and limitations that may arise from the complexity of these methods.

Research on Multi-Objective Evolutionary Algorithms Based on Large-Scale Decision Variable Analysis

Large-scale high-dimensional many-objective optimization problems (LaMaOPs) are prevalent in fields such as autonomous driving, cloud resource scheduling, and smart grids. LaMaOPs involve a large number of decision variables and multiple conflicting objectives that need to be optimized simultaneously. The challenges posed by the curse of dimensionality due to the vast number of decision variables, and the conflict between convergence and diversity caused by the numerous objective variables, make traditional optimization methods inadequate. To address these issues, this paper proposes a two-population cooperative evolutionary algorithm based on large-scale decision variable analysis (DVA-TPCEA). This algorithm integrates quantitative analysis methods for decision variables to deeply examine their impact on each objective and introduces a contribution-based objective detection method. Additionally, a dual-population cooperative evolution mechanism is employed, with targeted optimization strategies designed for convergence and diversity populations, achieving synergistic and complementary optimization between the two populations. To validate the algorithm’s effectiveness in practical applications, a large-scale container resource scheduling strategy based on the DVA-TPCEA algorithm is also proposed. The experimental results indicate that the proposed algorithm demonstrates significant advantages in both general datasets DTLZ, WFG, and LSMOP, and practical models.

Planning and Construction Strategies for Infrastructure in Traditional Villages of the Grand Canal from the Perspective of Villager Needs

The traditional villages along the Jiangsu section of the Grand Canal are facing the threat of decline and disappearance due to the decline of the canal transportation function and the advancement of urbanization, and it is urgent to study the protection and renewal of these villages. Based on the needs of villagers, this study aims to explore the planning and construction strategies of traditional village infrastructure in the Jiangsu section of the Grand Canal. Through a literature review, field investigation, and qualitative and quantitative analysis methods, this paper conducts in-depth research and data analysis on the status quo of six types of infrastructure in 29 traditional villages, including road traffic, water supply and drainage, garbage sanitation, energy utilization, postal communication, and ecological disaster prevention. The research results show that, although the infrastructure construction has made some progress, there are still problems such as unreasonable planning, low construction quality, and the lack of cultural characteristics, which cannot fully meet the actual needs of villagers. Through a regional comparative analysis, it is found that the infrastructure condition of the Jiangnan Canal section is better than that of the Huaiyang Canal section and Middle Canal section, but they all face challenges of protection and renewal. Based on the needs of villagers, this study puts forward corresponding protection and optimization strategies, which provide theoretical guidance and practical methods for the sustainable development of traditional village infrastructure, and it has important reference significance for the infrastructure protection and development of traditional villages in other regions.

Use of spectral transmittance model to improve the detection accuracy of chromium in soil

As a new quantitative analysis method for heavy-metal elements in soil, the main function of the polarization resolution model is to filter out the disturbance of other elements on the spectral signal of target plasma. In order to quantify the mechanism of improving detection performance, the spectral transmittance of plasma intensity in the polarization-resolved optical path has been derived, and the relationship between the intensity of polarization-resolved laser-induced breakdown spectroscopy (PRLIBS) and the characteristic peak wavelength has been defined. Using the spectral data in the wavelength range of 424.50–429.24 nm as the characteristic signal, a quantitative analysis method for detection of the Cr element in soil has been developed. The improvement of spectral intensity stability at the characteristic peak of Cr I 425.7 was analyzed, and the mechanism of enhancing the detection accuracy was elucidated. Research has shown that, based on the polarization characteristics of Cr element plasma, PRLIBS is not affected by the matrix effects of soil and characterizes the amplitude conversion from the reference concentration of Cr element to the plasma spectral intensity. The spectral transmittance of plasma spectra depends not only on the characteristic peak wavelength and complex refractive index of heavy-metal elements but also on the measurement conditions such as spatial geometric angles and reflectivity of the transmission medium.

Communication Strategies & Mobile Banking Adoption

This article, as research study, employed a mixed method research approach; which utilized both qualitative and quantitative methods of data collection and analysis. The utilised tools were an interview schedule and questionnaires. A target population of 3000 customers and 17 staff members from whom the sample of 353 respondents among the bank customers all 17 staff members purposively were selected. Simple stratified random sampling and purposive sampling were applied in selecting customers and staff members for the study respectively. Quantitative data collected was analysed using descriptive statistics and presented in form of tables, graphs and charts. The qualitative statistics were analysed thematically. Its findings revealed that good communication strategies influenced mobile banking adoption by enhancing the good corporate relationship with customers through word of mouth rated at 84.4 %, social media at 71.8%and mass media communication at 68.9%. It recommends creating awareness and elevating customers’ attitude by making the mobile banking platform affordable, easy and accessible to customers of all segments, easing the customers into the technology rather than forcing it on them while being innovative to stay competitive in the current market.

Thermo-electric coupling dynamic modeling and response behavior analysis of PEMEC based on heat current method

Complete analysis of the dynamic characteristics of the proton exchange membrane electrolytic cell (PEMEC) is significant for its efficient and flexible utilization. To fully reflect the dynamic process including thermo-electric interactions within PEMEC, this paper disassembles this process and simplifies it for representation through a clear diagram of dynamic power flow. On this basis, we proposed a novel combined qualitative and quantitative analytical method for the comprehensive response by defining the evaluating indexes for PEMEC's response performance. Meanwhile, we analyzed the change pattern of dynamic response behavior, response time and the influence of thermo-electric interaction under multi-scenarios, like different voltage abrupt change magnitudes, different cathode operating pressures, and different inlet water temperatures. The results show that the PEMEC has the biggest response behavior with the longest response time under the largest external voltage variation magnitude. Besides, there is the shortest response time and smallest parameters total changes after response when the cathode operating pressure is 15bar Moreover, when the inlet water temperature is 40 °C it has the characteristic of quick action time and small response magnitude. The model, analysis method, and findings in this paper provide an effective reference for the operational regulation of PEMEC's thermal and electrical parameters.

Numerical Simulation of Electromagnetic Nondestructive Testing Technology for Elasto-Plastic Deformation of Ferromagnetic Materials Based on Magneto-Mechanical Coupling Effect.

A numerical tool for simulating the detection signals of electromagnetic nondestructive testing technology (ENDT) is of great significance for studying detection mechanisms and improving detection efficiency. However, the quantitative analysis methods for ENDT have not yet been sufficiently studied due to the absence of an effective constitutive model. This paper proposed a new magneto-mechanical model that can reflect the dependence of relative permeability on elasto-plastic deformation and proposed a finite element-infinite element coupling method that can replace the traditional finite element truncation boundary. The validity of the finite element-infinite element coupling method is verified by the experimental result of testing electromagnetic analysis methods using TEAM Problem 7. Then, the reliability and accuracy of the proposed model are verified by comparing the simulation results under elasto-plastic deformation with experimental results. This paper also investigates the effect of elasto-plastic deformation on the transient magnetic flux signal, a quantitative hyperbolic tangent model between Bzpp (peak-peak value of the normal component of magnetic flux signal) and elastic stress, and the exponential function relationship between Bzpp and plastic deformation is established. In addition, the difference and mechanism of a magnetic flux signal under elasto-plastic deformations are analyzed. The results reveal that the variation of the transient magnetic flux signal is mainly due to domain wall pinning, which is significantly affected by elasto-plastic deformation. The results of this paper are important for improving the accuracy of quantitative ENDT for elasto-plastic deformation.

Achieving successful gas plant construction: A risk modelling framework with quantitative risk-based approach to schedule management

The construction of gas plants often experiences delays caused by various factors, which can lead to significant financial and operational losses. This research aims to develop an accurate risk model to improve the schedule performance of gas plant projects. The model uses Quantitative Risk Analysis (QRA) and Monte Carlo simulation methods to identify and measure the risks that most significantly impact project schedule performance. A comprehensive literature review was conducted to identify the risk variables that may cause delays. The risk model, pre-simulation modeling, result analysis, and expert validation were all developed using a Focused Group Discussion (FGD). Primavera Risk Analysis (PRA) software was used to perform Monte Carlo simulations. The simulation output provides information on probability distribution, histograms, descriptive statistics, sensitivity analysis, and graphical results that aid in better understanding and decision-making regarding project risks. The research results show that the simulated project completion timeline after mitigation suggested an acceleration of 61–65 days compared to the findings of the baseline simulation. This demonstrates that activity-based mitigation has a major influence on improving schedule performance. This research makes a significant contribution to addressing project delay issues by introducing an innovative and effective risk model. The model empowers project teams to proactively identify, measure, and mitigate risks, thereby improving project schedule performance and delivering more successful projects.

Integration of bifunctional silver dendrite membranes with surface-enhanced Raman scattering for sensitive detection of polystyrene microplastics in aquatic environments

Microplastics (MPs) are emerging environmental pollutants that are present in aquatic environments and accumulate within the food chain, posing significant threats to human health. Over 8 million tons of MPs enter these ecosystems annually. However, existing rapid qualitative and quantitative analytical methods for trace MPs are limited, hindering comprehensive research on their impact in water environments. This study presents a novel composite membrane with both adsorption and filtration functions, integrated with surface enhanced-Raman scattering technology for detecting trace MPs in water. The silver dendrites, modified with n-hexanethiol and loaded onto filter paper, facilitate enhanced enrichment and simultaneous sensitive detection of MPs. The composite membrane exhibited excellent retention rates for standard polystyrene (PS) MPs of various sizes (200, 500, and 1000 nm), achieving high enrichment efficiency. Sensitive detection was realized with a linear response in a concentration range of 0.01 to 0.5 g/L, yielding optimal enhancement factors exceeding 2.92 × 103, enabling detection at μg/L levels. Recovery rates for PS in spiked environmental water samples ranged from 96.86 % to 102.96 %. This innovative method offers a promising approach for the rapid and sensitive detection of trace MPs in aquatic environments, contributing significantly to the assessment of MPs pollution.

Comparison of Profit Sharing Schemes and Opsen on PKB and BBNKB Receipts in East Java

This study analyzes the impact of the implementation of Opsen Motor Vehicle Tax (Pajak Kendaraan Bermotor/PKB) and Motor Vehicle Transfer Fee (Bea Balik Nama Kendaraan Bermotor/BBNKBP) on regional revenues of districts/cities in East Java. Using a quantitative approach and comparative analysis method, this study compares the revenue sharing scheme with Opsen based on the realization data of PKB and BBNKB in 2023. The simulation results show that the implementation of Opsen increases district/city revenues in aggregate by 10.08%, but decreases provincial revenues by IDR 0.41 trillion. The city of Surabaya experienced the highest increase in revenue, which was 73.25%, while Pacitan experienced the deepest decline. This difference is due to the number of motor vehicles registered in each region. This has the potential to cause horizontal income inequality between regions. However, these results are in line with the objectives of fiscal decentralization, namely strengthening local taxing power. However, an appropriate cost-sharing mechanism is needed to maintain the quality of PKB and BBNKB collection services. This study also found that the results differ from previous studies which concluded that Opsen always significantly increases regional revenues. These findings provide important implications for designing fairer and more sustainable fiscal policies at the regional level.