Method For Quantitative Analysis Research Articles

The tesselle Project: A Collection of R Packages for Research and Teaching in Archaeology

Abstract The use of programming languages in archaeological research has witnessed a notable surge in the last decade, particularly with R, a versatile statistical computing language that fosters the development of specialized packages. This article introduces the tesselle project (https://www.tesselle.org/), a comprehensive collection of R packages tailored for archaeological research and education. The tesselle packages are centered on quantitative analysis methods specifically crafted for archaeology. They are designed to complement both general-purpose and other specialized statistical packages. These packages serve as a versatile toolbox, facilitating the exploration and analysis of common data types in archaeology—such as count data, compositional data, or chronological data—and enabling the construction of reproducible workflows. Complementary packages for visualization, data preparation, and educational resources augment the tesselle ecosystem. This article outlines the project's inception, its objectives, design principles, and key components, along with reflections on future directions.

The effect of digital transformation on the performance of the banking sector in Kazakhstan

This paper examines the impact of banking digitization on the development of the banking industry, particularly on banking performance. This study aims to identify critical factors for the development of financial banks and factors for the development of banking digitization in the banking sector of Kazakhstan. Based on this purpose, the core of banking digitization and its definition will be examined. The study conducted a comprehensive analysis that provided quantitative and qualitative characteristics of the development of digital technology and its impact on the development of the banking industry. The problems set out in this paper are solved using quantitative and financial analysis methods. The point index method was used during the study. Data from Halyk Bank’s annual reports from 2019 to 2023 were used to assess digitalization's penetration into the banking industry. A panel approach is also used, allowing for data analysis for individual banks. Our research concludes that bank digitalization clearly impacts bank performance, focusing on the number of digital banking users, digital banking transactions, and IT investment growth on bank performance (such as return on equity, RoAE). The research findings provide implications for the practice of digital transformation of banks, especially in terms of digital investment and performance improvement. This study lays a foundation for future research on the impact of digital transformation on bank performance and provides a reference for investment decisions in the Kazakhstan banking industry.

Child Marriage in Chepang Community of Ichachhakamana Rural Municipality, Chitawan, Nepal

This article examines the issue of child marriage within the Chepang community of Ichchhakamana Rural Municipality in Chitawan. The research employed primary and secondary data, applying quantitative and qualitative analytical methods. The legal framework in Nepal prohibits marriage for individuals under the age of 20. However, a significant majority, exceeding 90 per cent, of the surveyed individuals were found to have entered into marriage before reaching this age limit. Key contributors to child marriage identified in the study include poverty, insufficient awareness, and the influence of older individuals. The occurrence of child marriage presents considerable risks during the adolescent years, a time when individuals often become increasingly curious about sexual health and relationships. Therefore, awareness campaigns should focus primarily on this demographic. To effectively address the challenge of child marriage, it is vital to emphasize educational and awareness programs. Furthermore, the strict enforcement of existing laws is essential in the pursuit of eliminating child marriage.

A novel method for quantitative analysis of subjective experience reports: application to psychedelic visual experiences

IntroductionPsychedelic compounds such as LSD, psilocybin, mescaline, and DMT can dramatically alter visual perception. However, the extent to which visual effects of psychedelics consistently vary for different substances is an open question. The visual effects of a given psychedelic compound can range widely both across and within individuals, so datasets with large numbers of participants and descriptions of qualitative effects are required to adequately address this question with the necessary sensitivity.MethodsHere we present an observational study with narrative self-report texts, leveraging the massive scale of the Erowid experience report dataset. We analyzed reports associated with 103 different psychoactive substances, with a median of 217 reports per substance. Thirty of these substances are standardly characterized as psychedelics, while 73 substances served as comparison substances. To quantitatively analyze these semantic data, we associated each sentence in the self-report dataset with a vector representation using an embedding model from OpenAI, and then we trained a classifier to identify which sentences described visual effects, based on the sentences’ embedding vectors.ResultsWe observed that the proportion of sentences describing visual effects varies significantly and consistently across substances, even within the group of psychedelics. We then analyzed the distributions of psychedelics’ visual effect sentences across different categories of effects (for example, movement, color, or pattern), again finding significant and consistent variation.DiscussionOverall, our findings indicate reliable variation across psychedelic substances’ propensities to affect vision and in their qualitative effects on visual perception.

A stable method for ionic rare earth element extraction and quantitative analysis of total quantity and composition of batch samples.

The development of a stable, high-precision and batch ion-adsorption rare earth element detection method is highly anticipated in the delineation and evaluation of the mining value of rare earth element mines. In this study, a novel mixed extractant of ammonium sulfate + ammonium citrate + aceto-sodium acetate buffer was used to significantly improve the extraction efficiency of rare earth elements. Following a series of parameter optimizations, an off-line internal standard addition method and the collision mode of the inductively coupled plasma-mass spectrometer were used to improve the detection efficiency for batch samples, effectively eliminating oxide interference between the rare earth elements and improving the detection accuracy. The detection limit for ion-adsorption rare earth elements was 3.4 μg g-1 and the detection range was 12-8000 μg g-1. More importantly, the spiked and recovery experiments carried out in multiple laboratories with internal quality control samples show that the relative deviation was -5.61 to 3.79%, which indicates that the method has sufficient stability. Establishment of this method will help to improve the comprehensive utilization efficiency of rare earth resources and provide important support for rare earth element mining.

Makanan Khas Bali Di Desa Wisata Bakas Berpotensi Besar Dikembangkan Menjadi Wisata Gastronomi

Bakas Village is one of the tourist villages in Klungkung Regency, Bali, which has begun to offer gastronomic tourism attractions based on traditions that are still maintained by the local community, namely the tradition of cooking traditional Balinese cuisine. This study was conducted to produce a study that explains how Balinese cuisine can become gastronomic tourism in Bakas Tourism Village. This study was conducted using a primary survey method, namely field observation and interviews with key informants from Bakas Tourism Village. Data collection was supported by a checklist instrument consisting of 7 variables with 28 indicators based on qualitative descriptions from the Guidelines for the Development of Gastronomy Tourism book published by the United Nation World Tourism Organization (UNWTO). It was filled in using the Likert scale method with a score range of 1-5. Furthermore, the results of this checklist were described using quantitative and qualitative descriptive analysis methods. Based on observations and data processing, it was found that Bakas Tourism Village has great potential in developing gastronomic tourism. It's just that there are still several sectors that need to be fixed or developed again by Bakas Tourism Village in order to improve gastronomy in this village.

Italians and Global Warming Skepticism: opinions and Ways of information

Scientists, policy-makers, entrepreneurs, and citizens are strongly concerned about the harmful consequences of climate change. Individual beliefs about social norms and economic and political orientations regarding trust and social relationships call into question values ​​such as care for the environment, autonomy, freedom of choice, and risk. Given the influence of the media on public perceptions, it is essential to consider how, with what means, and towards which issues citizens orient themselves to address this epochal phenomenon. Using quantitative and qualitative methods of analysis, the present study investigates the characteristics and reasons of the individuals who are skeptical of the evidence of global warming in Italy and how the Italians inform themselves about this issue. Quantitative analysis was performed on two representative samples of 1011 and 1030 individuals from Observa Science in Society in 2022 and 2023 through a structural equation model (SEM) to study the dimensions associated with climate change skepticism. Qualitative research on a panel of 93 Italians selected by gender, cultural level, and area of residence further highlighted the information channels, methods of use, and the main dimensions of interest in climate change. This robust mixed-mode methodology, which ensures the credibility and reliability of the study's findings, is a key strength of this research. Our results confirm that less trust in science and older age are associated with skepticism. Furthermore, traditional media are the primary means of information despite the growing importance of social relations - including social networks - in shaping opinions on the environment and climate change. The conclusions also reveal that experts influence the public, even if personal experience often mediates this effect. These findings have practical implications for understanding and addressing climate change skepticism in Italy, equipping researchers, policymakers, and individuals interested in this issue with the knowledge to make informed decisions and take effective action.

Pengaruh Rekam Medis Elektronik Terhadap Efisiensi Pelayanan Kesehatan Poli Obgyn di RSU X

Electron Medical Records are essential for Health Services to ensure more efficiency and effectiveness in serving patients, especially in OBGYN Polyclinics. Having an Electronic Medical Record can make work easier. The aim of this investigation is to find out how electronic medical records influence the efficiency of health services. The research method employed a quantitative analytical observation design method. The population used was 2 doctors and 6 nurses at the ob-gyn polyclinic. The results from questionnaire and simple linear regression test revealed that it has a strong correlation and the Pearson correlation value is 0.704 and also the variables x and y have a significant influence. Then, it is found that the test done through SPSS version 26 was declared valid and reliable

Evaluating Approaches Employed by the Ministry of Finance in Tanzania to Enhance the Effectiveness of On-Job Training Programs

This paper evaluates the approaches employed by the Ministry of Finance in its on-the-job training programs using a qualitative approach. Specifically, the paper intended to; investigate the approaches employed by the Ministry of Finance in the design, implementation, and management of its on-job training initiatives, to assess the extent to which knowledge and skills acquired through OJT programs are successfully applied to employees' daily roles and responsibilities and to examine challenges and barriers faced by the Ministry of Finance in implementing OJT programs. The theory which was adopted in the paper is Human capital theory which suggests that investments in employee training and development can improve their productivity and skills, benefiting both the individual and the organization. The target population for this study was the 550 Ministry of Finance Employees at the headquarter. A case study research design was adopted, with a combination of random and purposive sampling techniques yielding a sample of 55 respondents. Data were collected through questionnaires, interviews, and documentary reviews, and analyzed using both quantitative and content analysis methods. The findings reveal that the Ministry has employed several strategies in designing, implementing, and managing these training programs. These strategies include tailoring training to specific job roles and career paths (90% of respondents), promoting continuous professional development (90% of respondents), offering leadership development programs (85% of respondents), providing performance-based training incentives (85% of respondents), integrating emerging technologies (82% of respondents), fostering cross-departmental collaboration, and promoting diversity and inclusion in training initiatives (75% of respondents). Employees have largely applied the skills and knowledge gained from these trainings; however, their effectiveness is often hindered by challenges such as limited managerial support, lack of time, insufficient feedback and recognition, and inadequate resources. Moreover, the overall effectiveness of the Ministry’s on-the-job training implementation is constrained by factors including time constraints, difficulties in identifying skills gaps, resource limitations, resistance to change, and a lack of training infrastructure. In conclusion, while the Ministry of Finance has demonstrated a commitment to implementing on-the-job training programs, the paper recommends that management should focus on ensuring the allocation of adequate financial resources, conducting effective training needs assessments to accurately identify skills gaps, and hiring more qualified and adequate professional trainers to enhance the effectiveness of these programs.

Perhitungan Harga Pokok Produksi Serta Harga Pokok Penjualan Terhadap Laba Penjualan: Studi Kasus pada UMKM Cilok Wonogiri

This research aims to determine the effect of production costs and cost of goods sold on profits generated by MSMEs in Cilok Wonogiri. The elements that form production costs are production costs, including: raw material costs, direct and indirect labor costs, general production costs and inventory of goods in process, including: inventory of goods in process and inventory of goods. ongoing. Meanwhile, the cost of goods sold factor includes total production costs and finished product inventory (initial finished product inventory and final finished product inventory). These factors will influence the selling price of the product. Primary and secondary data are the types of data used in research. Primary data was taken from direct observation of subjects to obtain accurate data along with the results of company interviews. Secondary data was collected through company records regarding data relating to production costs and cost of goods sold which will affect the profits obtained from sales of Wonogiri cilok. Researchers examine production costs using company calculations and production cost data for 2022. The analysis technique used by the author is a quantitative descriptive analysis method. Quantitative descriptive analysis is used to explain the calculation of production costs according to the full cost method, then this information is used as a basis for determining product selling prices to determine MSME profits.

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.

Differences in near-infrared fluorescence imaging and histological analysis of cheek mucosa in golden hamsters with different pathological states.

To explore and analyze the feasibility of using indocyanine green (ICG) near-infrared fluorescence (NIF) imaging technology for the early diagnosis of oral potential malignant disorders and oral squamous cell carcinoma. 7,12-Dimethylbenz[a]anthracene in acetone solution was used to induce various pathological models of buccal mucosal lesions (mild/moderate dysplasia, severe dysplasia, squamous cell carcinoma) in golden hamster. ICG-NIF was conducted for the quantitative analysis of the fluorescence signal of lesion tissue, and evaluation of the diagnostic and discriminative capabilities of the ICG-NIF technology for mucosal lesions in various pathological states. Immunohistochemical staining was perform to examine the microvessel density (MVD) and microlymphatic vessel density (MLVD) of mucosa in various pathological states and explore the histological reasons underlying the differences in fluorescence signals. The results of ICG-NIF fluorescence quantitative analysis reveal the higher fluorescence intensity of mucosal lesions in the experimental group compared with that of the normal mucosa on the control side, with statistical differences (P<0.05). Moreover, the more severe the malignancy of mucosal lesions in the experimental group, the higher the fluorescence intensity. According to histopathological analysis, the malignant progression of mucosal lesions in golden hamsters was accompanied with an increase in MVD (P<0.05) and a decrease in MLVD (P<0.05). The abnormal proliferation of mucosal lesions in golden hamsters exhibits a difference in ICG-NIF fluorescence signal compared with normal mucosal tissue. Fluorescence quantitative analysis methods can provide assistance in differentiation and show potential for clinical applications.

Forecasting Rate of Crime Using Machine Learning

Criminalities and predicting are indispensable when it comes to crime identification and prevention, and recognition of areas with a high probability of criminal occurrences, as well as simulation of crime scenes. Finally, and based on the methods of data mining, patterns can be obtained from large amount of unstructured data that can help in predicting future crimes. Crime is still a social issue that impacts the population on all the main aspects including quality of life, economic growth, and image of the nation, and thus, calls for more elaborate and effective systems and strategies for the safety of the population. With the help of the DM techniques proposed below, the goal is to design a system that is capable of identifying, studying, and these predicting types of crimes in certain areas. In particular, the current paper focuses on the methodological approaches of crime analysis and crime forecast. Thus, this work examined temporal and spatial features of crime to establish patterns and trends necessary to predict subsequent occurrences. Classification, clustering and association rule mining are utilized mainly in crime data classification process, in order to make distinctions and identify relationships between certain crime characteristics. Quantitative methods of analysis which include regression analysis, decision trees and artificial neural networks forecast future formulations of criminal incidences

Research on the Economic Radiation Measurement of Surrounding Cities in the Guangdong Hong Kong Macao Greater Bay Area

By establishing a comprehensive index system of cities, this paper uses gravity model to measure the economic connection intensity of cities in Guangdong Province, and divides cities into four levels by k-means clustering analysis. The first level city is Guangzhou, which ranks first in the total economic connection intensity of the whole Guangdong Province. The second tier cities are Shenzhen and Foshan; The third tier cities are Dongguan, Zhuhai, Zhongshan, Jiangmen and Huizhou. The rest of the cities ranked fourth. Combining qualitative and quantitative analysis methods, this paper puts forward two suggestions on "measuring the economic radiation of the Guangdong-Hong Kong-Macao Greater Bay Area to the surrounding cities" : strengthening the economic strength and strengthening the radiation subjects; Make use of location advantages to improve traffic accessibility.

The Use of "Seven" as an English Learning Medium for 7th Grade Junior High School Students

This article focuses on the development of mobile learning media using Android-based applications to enhance the teaching and learning process, specifically for English language education in seventh-grade classrooms. The study follows the research and development (R&amp;D) model proposed by Lee and Owens (2004) and was conducted in two private schools in the Malang district. The development process consists of five phases: assessment/analysis, design, development, implementation, and evaluation. The "Seven" application, developed using the Andromo platform, aims to improve the four basic skills of English language learning: reading, speaking, writing, and listening. The effectiveness of the application was evaluated through material verification and media verification, using qualitative and quantitative data analysis methods. The findings indicate that the "Seven" application was well-received by students, with positive feedback regarding its user-friendly interface and the engaging learning experience it provided. The study demonstrates the potential of Android-based mobile learning as an effective and practical tool for enhancing English language education in seventh-grade classrooms.

A unique cuvette and near-infrared spectral imaging for fast and accurate quantification of milk compositions

Analyzing the nutritional compositions of milk using traditional methods is costly, time-consuming, and impractical for rapid field measurements, resulting in delays in quality control procedures. This paper presents a rapid, accurate, and easy-to-use method for quantitative analysis of finished milk compositions using a low-cost, portable, and environmentally friendly measurement system. The system uses a near-infrared (NIR) broadband digital camera to capture spectral images of milk after it is placed in a customized cuvette in the short-wave NIR region (700–1050 nm). A machine learning algorithm that combines image edge detection and gradient-boosted decision trees then regresses these images to predict the protein and fat content of the milk. Each measurement requires a maximum of 1.75 mL of milk sample with no additional consumables and takes 0.1 s to complete. The coefficient of determination (R2CV) for the fat detection model was 0.999 and the root mean square error (RMSECV) was 0.026 g/100 mL. For protein detection, the R2CV was 0.957 and the RMSECV was 0.058 g/100 mL. The experimental results show that the system achieves high precision and stability while realizing miniaturization and portability.

Tracheloside, the main constituent of the total lignan extract from Trachelospermi Caulis, inhibited rheumatoid arthritis via IL-17/MAPK signaling pathway

A quantitative analysis method was established using high-performance liquid chromatography (HPLC) to simultaneously determine five lignans in the total lignan extract (TLE) from Trachelospermi Caulis at 280 nm, including nortracheloside, tracheloside, nortrachelogenin, trachelogenin, and arctigenin. The method demonstrated good linearity for each lignan within their respective ranges, with precision, stability, and repeatability meeting the criteria for quantitative analysis. Tracheloside, the most abundant compound in the TLE, effectively inhibited the release of inflammatory factors IL-6 and IL-17, and suppressed the migration MH7A cells in vitro. Furthermore, tracheloside reduced the production of key inflammatory factors, including COX-2, IL-6, IL-17, MMP2, MMP3, MMP9, JNK, p-JNK, p38, and p-p38 in TNF-α induced MH7A cells, thereby inhibiting the IL-17/MAPK signaling pathway, and thus contributing to its anti-rheumatoid arthritis effects. This study represents the first report on the simultaneous quantification of five major lignans from Trachelospermi Caulis and the anti-inflammatory properties of tracheloside.

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.

Analysis of Factors Influencing Pregnant Women's Participation HIV Screening in Indonesia

Indonesia is the third largest contributor of HIV/AIDS sufferers in Asia Pacific, after India and China. Several factors that can influence HIV screening in pregnant women include education, knowledge, attitudes about HIV screening, family support and support from health workers. This study aims to analyze the factors that influence the participation of pregnant women in HIV screening in Indonesia in 2024. This study uses a quantitative analysis method with a cross-sectional design. The research sample was 35 respondents in the first trimester of pregnancy using a purposive sampling technique. The research instrument used a questionnaire. The data used is primary data analyzed using the chi square test. The results of the univariate analysis showed that 62.90% of pregnant women underwent HIV screening, with a high level of education of 58.4%, good knowledge of 56.70%, positive attitudes of 58.00%, family support of 55.1%, and support from health workers of 55.90%. Pregnant women are expected to be able to actively seek information related to HIV screening other than from health workers or from various media so that they can have high participation in participating in the implementation of HIV screening examinations as an effort to detect HIV early.

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 &lt; t-table (0.824 &lt; 2.018) with a significance of 0.415 &gt; 0.05. Similarly, the analysis shows that Return on Equity (ROE) also does not significantly influence stock prices, with a t-value &lt; t-table (-0.919 &lt; 2.018) and a significance of 0.364 &gt; 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.