Correspondence Analysis Method Research Articles

Impacts of Soil Properties on Species Diversity and Structure in Alternanthera philoxeroides-Invaded and Native Plant Communities.

Soil properties can affect plant population dynamics and the coexistence of native and invasive plants, thus potentially affecting community structure and invasion trends. However, the different impacts of soil physicochemical properties on species diversity and structure in native and invaded plant communities remain unclear. In this study, we established a total of 30 Alternanthera philoxeroides-invaded plots and 30 control plots in an area at the geographical boundary between North and South China. We compared the differences in species composition between the invaded and native plant communities, and we then used the methods of regression analysis, redundancy analysis (RDA), and canonical correspondence analysis (CCA) to examine the impacts of soil physicochemical properties on four α-diversity indices and the species distribution of these two types of communities. We found that A. philoxeroides invasion increased the difference between the importance values of dominant plant species, and the invasion coverage had a negative relationship with the soil-available potassium (R2 = 0.135; p = 0.046) and Patrick richness index (R2 = 0.322; p < 0.001). In the native communities, the species diversity was determined with soil chemical properties, the Patrick richness index, the Simpson dominance index, and the Shannon-Wiener diversity index, which all decreased with the increase in soil pH value, available potassium, organic matter, and ammonium nitrogen. However, in the invaded communities, the species diversity was determined by soil physical properties; the Pielou evenness index increased with increasing non-capillary porosity but decreased with increasing capillary porosity. The determinants of species distribution in the native communities were soil porosity and nitrate nitrogen, while the determinants in the invaded communities were soil bulk density and available potassium. In addition, compared with the native communities, the clustering degree of species distribution in the invaded communities intensified. Our study indicates that species diversity and distribution have significant heterogeneous responses to soil physicochemical properties between A. philoxeroides-invaded and native plant communities. Thus, we need to intensify the monitoring of soil properties in invaded habitats and conduct biotic replacement strategies based on the heterogeneous responses of native and invaded communities to effectively prevent the biotic homogenization that is caused by plant invasions under environmental changes.

Innovation policy for sustainability transitions in small economies: Energy technology innovation in Hong Kong

In this paper, we analyzed Hong Kong's sustainable energy transitions innovation policy, and compared it to the policies in 11 small, high-income jurisdictions. To do this, we identified 696 innovation interventions implemented between 2008 and 2020. We classified them into 42 types of policy instruments. Then we visualized the policy mixes of the jurisdictions with the assistance of correspondence analysis methods. The results suggest that Hong Kong's overall policy mix heavily relies on overarching policy strategies to guide research and demand side policies to support energy technology adoption. However, Hong Kong's support for research and development of domestic clean energy technologies to overcome the so-called “valley of death”, a critical gap between public and private support, remains limited. This contrasts with the policy mixes of more innovative peer jurisdictions, which provide R&D funding and business support targeted at encouraging clean energy technologies and facilitating connections across the innovation system.

Blood and Micronuclei Analysis of Tawes Fish (Barbonymus gonionotus) Correlation with Water Quality in the Boon Pring Ecotourism Area, Turen, Malang Regency

Tawes (Barbonymus gonionotus) is a type of endemic fish that lives in the Boon Pring Reservoir, Turen, and Malang Regency. This study aims to analyze the water quality and blood profile of Tawes Fish (Barbonymus gonionotus) in Boon Pring Ecotourism and to determine the relationship between water quality and fish health through their blood profile using the Canonical Correspondence Analysis (CCA) method. The results obtained after measuring the water quality during two samplings at both locations were that the temperature ranged from 21.7–27C, TDS 111–145 mg/l, TSS 2-4 mg/l, pH 6-6.7, DO 8–10.1 mg/l, BOD 0.44-0.98 mg/l, and ammonia 0.026–0.075 mg/l. Both locations are classified as having good or normal conditions. Observations on the blood profile of Tawes fish (Barbonymus gonionotus) are healthy and normal. The average number of erythrocytes was 2,586,667 cells/mm3, leukocytes were 60,500 cells/mm3, lymphocytes were 76.8%, monocytes were 1.4%, neutrophils were 3.3%, hemoglobin was 9.8 g/mL, hematocrit was 34.6%, and micronuclei were 12.3 cells/1000. The results of data analysis using CCA showed that all blood and micronuclei profiles of fish were affected by water quality parameters, both significantly and moderately to severely.

Spatiotemporal characteristics and influencing factors of airport service quality in China

Airport service quality (ASQ) is essential for determining the quality of ground civil aviation services. In this study, ASQ was assessed using the monthly airport aviation complaint data from 2015 to 2019 of 196 airports in mainland China (except for airports in Hong Kong, Macao, and Taiwan, which are not included in the statistics). First, we constructed a seasonal index of aviation complaints to evaluate and compare the overall temporal characteristics of ASQ in China. Second, the spatial distribution pattern of ASQ in China was determined using the aviation complaint concentration index and hot spot analysis model. Finally, the major influencing factors and categories of ASQ in China were analyzed considering spatiotemporal dimensions using the correspondence analysis method. The results revealed that there were clear seasonal differences among ASQ in China, with a high–low–low–high distribution during all four seasons. The regional agglomeration trend of airport aviation complaints was obvious, and the spatial difference in ASQ was large. Northern and western China performed better than southern China. Spatiotemporal and influencing factors of ASQ were the most strongly correlated factors in each quarter and region. The predominant source of aviation complaints across all types of airports is related to fundamental services, with check-in services identified as the most impactful category affecting ASQ. This study, based on 60 months of statistical data, offers a comprehensive evaluation of ASQ throughout the entire airport network in mainland China, from the perspective of aviation complaints. Additionally, a systematic ASQ evaluation method and research system encompassing time, space, and elements were established. This framework not only stimulates the improvement and enhancement of ASQ but also provides a theoretical foundation for differentially enhancing ASQ in regional airports. Overall, our results contribute to breaking through the qualitative research thinking system in ASQ research from a theoretical perspective, paving the way for exploring broader research in enhancing the quality of ground civil aviation services.

The Perception of the Biocentric Tourist Landscape in “Pueblos Mágicos” According to Inhabitants

The “Pueblos Mágicos” program designation, given by the Mexican government to towns that have kept their cultural heritage, as a local public policy makes changes to residents, the economy, and the space. Consequently, it creates a new landscape. To explain the repercussions on the population, their perception is analyzed, a process that allows judgments to be made about the environment. Therefore, the objective is to explain the changes in the perception of the biocentric tourist landscape according to the inhabitants of the “Pueblo Mágico” of Jiquilpan, Michoacán. For the methodology, a quantitative approach was chosen, through a survey on the topics of residents, the economy, and space in the area where tourist goods and services are concentrated. The analysis used was multivariate with a multiple correspondence analysis method. The results are shown through dimension graphs showing the iterations and their contributions, and topics and questions are displayed by their contribution value through centrality schemes. Among the findings, there is a negative perception of the biocentric landscape among the residents of the historic center in Jiquilpan. However, they are in favor of coexisting with tourists and the improvement of public services as well as with good restaurants and hotels. Conversely, they are against the actions that were carried out by public administrations.

Will Development and Temperature be Reconciled?

The country’s advancement is fueled by regional growth. It frequently has many detrimental effects in its application, including contamination. Climate, notably temperature, is negatively impacted by the ensuing pollution. This study uses the Multiple Correspondence Analysis (MCA) method to measure the pollution index, followed by the instrumental variable (IV) method to calculate the effect of development on pollution and temperature. Rural data from Podes 2018 is among the data used in this investigation. The findings of this study show that developed and developing areas are where the negative pollution index forms the most frequently. The construction and the resulting pollution index have a negative impact on temperature. The development process should pay attention to environmental aspects to anticipate worse temperature changes in the coming period.

체육수업에 참여하는 고등학생의 신체적 자기개념 인식간 상호관계 분석

This study aims to identify the main predictors of the impacts of the application of the Physical Activity Promotion System program on the physical self-concepts of high school students in a school physical education classroom setting. The study population included 175 students from J. High School located in C. Independent samples t-test and one-way analysis of variance (ANOVA) were used to analyze the impacts of gender and physical fitness level on physical self-concept scores of high school students, and the correspondence analysis method was used to identify the relationships among the sub-factors of the students’ perceptions of the choices and decisions of their physical self-concepts.&#x0D; The results of the study are as follows.&#x0D; First, there were no significant differences in physical self-concept scores between gender and fitness level. Second, although the perceptions of physical self-concept change according to gender and physical fitness level were generally positive, there were some areas (cardio-respiratory endurance, flexibility, strength and muscular endurance, physical activity, overall body, appearance, and body fat) that would require customized guidance activities to improve physical fitness.

Creating Order or Revealing Disorder? Some Preliminary Results Using Multiple Correspondence Analysis (MCA) in Studying Archaeological Boat Finds from Norway (AD 1050–1700)

Abstract This article discusses the use of statistical methods for systematising 96 archaeological ship finds, mainly from the southern and south-eastern coast of Norway. It draws on an article published in 2009 by Jan Bill, where he did a similar investigation of material from the Danish area. The method of multiple correspondence analysis (MCA) provides a way to summarise categorical data in a reduced number of dimensions. The results are presented in a geographical space, a plot, that can be used for making interpretations and assumptions of cohesions and divergences in the material. It is a way of analysing continuity and change in boatbuilding techniques that avoids using arbitrary and ambiguous concepts of historical (ship) types. Instead, the building techniques, the ways of ‘doing things’, make the premises for classification. The results in this article can be considered preliminary, its primary function being a discussion on methodology.

Correspondence Analysis to Visualize the Relationships between Alpha-S1 Casein and Beta-Lactoglobulin Gene Polymorphisms in Norduz Sheep

Correspondence analysis (CA) is one of the multivariate statistical analysis techniques which examines the relationships between different nominal variable categories in two-way or contingency tables. The aim of this study is to investigate the relationships between Alpha-S1 casein and Beta-lactoglobulin gene polymorphisms in Norduz sheep by the CA method. In this study, genotype frequencies of CSN1S1 and BLG genes in Norduz sheep (n=102) were used as categorical variables. As a statistical method, descriptive statistics of characteristics were presented as count and percent and the chi-square ( 𝜒 2 ) test and CA in this study were performed to explore the relationships among the genotype frequencies of Beta-lactoglobulin and Alpha-S1 casein genes. The results of this study indicated that CA can be contributed to a graphical display for categories of nominal variables. Animal breeders can utilize CA as an analytical technique and graphical representation for categorical data. According to the results of this study, the first and second dimensions jointly accounted for 52.25% of the total inertia and "AA" allele of CSN1S1 has the greatest significance in the first dimension, while "BB" allele of BLG has the greatest significant in the second dimension. Therefore, it would be useful to investigate the effects of βLactoglobulin and αS1-Casein genotypes on various yield traits in larger population of Norduz sheep.

East-West differences in experienced corporal punishment: Results of a representative German study

Due to the division of Germany into the German Democratic Republic and the Federal Republic of Germany following the Second World War, large parts of the population of today's Germany were socialized under different socio-economic, political, and legal conditions, which could possibly lead to different experiences with corporal punishment as a method of education. In this paper, we investigate whether being socialized in East or West Germany, respectively, had an influence on childhood experience of corporal punishment. The evaluation is based on a representative German survey (n = 2331) carried out in 2020. In order to investigate the dimensionality of the experience with corporal punishment, we used the method of multiple correspondence analysis. The structures which were discovered using multiple correspondence analysis were subsequently verified using confirmatory factor analyses. We then examined the influence of explanatory variables on different parental punishment styles in a structural equation model. Three main parental punishment styles were identified: non-corporal punishment, mild punishment, and severe punishment. Respondents who were socialized in East Germany had a lower probability of having experienced severe punishment and non-corporal punishment compared to those socialized in West Germany. Our analysis also showed that corporal punishment tended to be more frequently practiced by younger mothers and older fathers. The results of this study indicate that legal regulations regarding non-violent child-raising are not just symbolic, but do indeed have a measurable influence on the educational methods of parents.

Multidimensional Energy Poverty in China: Measurement and Spatio-Temporal Disparities Characteristics.

As the world's most populous country, China's energy poverty reduction achievements directly impact the global energy poverty reduction process. Analyzing energy poverty in China is therefore critical to consolidating the results of poverty eradication, eliminating relative poverty, and improving the social welfare of residents. However, prior research neither considered the applicability of existing energy poverty indicators to the current Chinese reality, nor the spatiotemporal disparities of energy poverty using micro-level data. To study the dynamics of energy poverty in China at the household level, a new multidimensional energy poverty index is constructed with seven dimensions using multiple correspondence analysis methods. Furthermore, provincial disparities and characteristics of energy poverty are compared using a spatial autocorrelation analysis method. The findings show that energy poverty has improved in China from 2012 to 2018, but its incidence and intensity remain high. Moreover, significant regional differences in energy poverty exist between different regions of China. High levels of energy poverty are mainly concentrated in the western and northeastern regions (especially in rural areas), and the urban-rural gap shows a similar pattern. The results obtained from spatial autocorrelation analysis demonstrate that China's energy poverty exhibits significant spatial clustering characteristics. Further, the results of standard deviation ellipse show that during the study period, the center of gravity of energy poverty in China was in Henan province and gradually shifted to the northwest. These findings help policymakers to formulate specific energy poverty reduction policies for various groups affected by energy poverty.

Nonlinear canonical correspondence analysis and its application

The canonical correspondence analysis (CCA) is a multivariate direct gradient analysis method performing well in many fields, however, when it comes to approximating the unimodal response of species to an environmental gradient, which still assumes that the relationship between the environment and the weighted species score is linear. In this work, we propose a nonlinear canonical correspondence analysis method (NCCA), which first determines the most appropriate nonlinear explanatory factor through two screenings by correlation and LASSO regression, and successively uses the linear regression method and the improved heuristic optimal quadratic approximation method to fit the chi-square transformation values of the response variables. Thus, our method effectively reflects the nonlinear relationship between the species and the environment factors, and a biplot is employed to visualize the effects of the later on the distribution of species. The results from applying this method over a real dataset show that the NCCA method not only maintains the advantages of the polynomial canonical correspondence analysis (PCCA) proposed by Makarenkov (2002), but also outperforms Makarenkov’s method in explaining the variance of response variables.

Extraction of Novel Bioactive Peptides from Fish Protein Hydrolysates by Enzymatic Reactions

Bioactive peptides derived from fish the byproduct protein hydrolysate have wide potential as functional food ingredients. The preparation of bioactive peptides is commonly achieved via enzymatic hydrolysis; this is the most preferred method because it has high specificity, fewer residual organic solvents in the product, and it is usually carried out in mild conditions. The use of various enzymes such as proteases is widely practiced in the industry, yet there are various limitations as it is of high cost and there is a limited availability of food-grade enzymes in the market. Moreover, high-throughput purification and the identification analysis of these peptides are currently being studied to further understand the functionality and characterization of the bioactive peptides. This review mainly focuses on the novel bioactive peptides derived from fish protein hydrolysates from various fish wastes and byproducts. The hydrolysis conditions, source of hydrolysate, and amino acid sequence of these novel peptides are presented, along with their corresponding methods of analysis in purification and identification. The use of various enzymes yields novel peptides with potent bioactivities, such as antiproliferative, antimicrobial, antihypertensive, antiglycemic, antitumor, and antioxidative biological functions. The increasing interest in proteomics in marine and aquatic waste utilization continues due to these products’ bioactivity and sustainability.

Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data.

Controlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient's genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched to groups of various MII oocyte counts using ranking, correspondence analysis, and self-organizing map methods. The gradient boosting machine technique was used to train models on a clinical dataset of 8,574 or a clinical-genetic dataset of 516 ovarian stimulations. The clinical-genetic model predicted the number of MII oocytes better than that based on clinical data. Anti-Müllerian hormone level and antral follicle count were the two most important predictors while a genetic feature consisting of sequence variants in the GDF9, LHCGR, FSHB, ESR1, and ESR2 genes was the third. The combined contribution of genetic features important for the prediction was over one-third of that revealed for anti-Müllerian hormone. Predictions of our clinical-genetic model accurately matched individuals' actual outcomes preventing over- or underestimation. The genetic data upgrades the personalized prediction of ovarian stimulation outcomes, thus improving the in vitro fertilization procedure.

Integration of fractal modeling and correspondence analysis reconnaissance for geochemically high-potential promising areas, NE Iran

Most geochemical and geostatistical analysis in mining exploration requires removing regional trends in order to obtain local anomalies. In this paper, stream sediment samples, which collected from Khusf area (NE Iran), was studied based on Concentration-Area (C-A) fractal model as well as correspondence analysis methods to find high-potential areas elements. Correspondence analysis with 170 samples through 20 elements concentration values in each sample was performed. According to correspondence analysis, among one or several elements in the study area, local anomalies were separated which the highest concentration relates to the variables Pb, As, and Cd elements. After the correspondence analysis, the best variogram for the Khusf area was studied. Elemental concentration maps was then produced through estimating the values using kriging method. Therefore, using the fractal method, between three statistical sets of elements, it was concluded that the third set showed the anomaly for Pb, As, and Cd elements with local anomaly values respectively determined as 55, 7.2, and 0.88 ppm. Although Cd element is not genetically related to same source of Pb and As, utilizing integrated approach, Cd anomalies has also been detected in the area as a promising element zone. Finally, it is suggested that this region has the possibility of Basic Metals occurrence and suggests further geophysical operations on a local identification scale.

Consumers’ Behavior in the Field of Organic Agriculture and Food Products during the COVID-19 Pandemic in the Czech Republic: Focus on a Comparison of Hyper-, Super- and Farmers’ Markets and Direct Purchases from Producers

The aim of this paper is to assess Czech food consumers’ behavior when buying organic products during the COVID-19 pandemic, with an emphasis on the place of purchase of organic agriculture and food products—especially those purchases with the shortest logistics value chain, i.e., purchase at farmers’ markets, or directly from the producer—and a comparison with the current most common places of purchase of organic products in the Czech Republic, supermarkets and hypermarkets. Categorical data analysis methods were used to create a profile of the consumer according to the most frequent purchase locations. To create mathematical–statistical models and interpretations, the methods of logistic regression, correspondence analysis and contingency table analysis were chosen. According to the results of the survey, respondents under 25 years of age are the least likely to make purchases at farmers’ markets or directly from the producer. Consumers aged 26–35 and with a university degree are the most likely to buy organic agriculture and food products at this location, followed closely by older respondents in the categories 36–45 and 46+ and with a secondary education. It is important for manufacturers to have an overview of where, in what quantities, and for what reasons consumers buy their products, especially for reasons of production optimization and planning, ecological concerns, rural development, and the impact on local areas and the value chain.

The Impact of the COVID-19 Pandemic on the Labour Market in the Hotel Industry: Selected Conditions in Poland

Examining selected aspects of labour market performance in the Polish tourism sector can extend our knowledge of hotel company attitudes in connection with COVID-19. The aims of this article are to present selected determinants of labour market performance in the Polish tourism sector (with particular emphasis on the hotel industry) in the era of the COVID-19 pandemic and to address the following research question: how did the COVID-19 pandemic affect the functioning of hotel companies in the key tourist region of Poland—Zachodniopomorskie province? The research methods used in the study included critical analysis of source literature, survey method, correspondence analysis method, and analysis of primary and secondary data, mainly from official statistics. The survey was conducted in January 2022. Information was collected from 129 respondents using surveys. The results of the research presented in the article reveal that the observed long-term upward trend in the national labour market has been halted by the pandemic and that (among the various accommodation facilities) hotels are the most vulnerable to changes in the tourism labour market. The authors’ contributions to the literature are the identification of the extent to which businesses from the hotel industry have been affected by the COVID-19 pandemic and the determination of the impact of the pandemic on selected employment-related aspects of business operations in Zachodniopomorskie province.

Safety Assessment of Speed Governing Systems in Hydroelectric Power Plants: A Functional Safety Perspective

In line with the advancing technology, reliability has become one of the critical factors to be taken into consideration by the operators in the energy sector to minimize losses regarding cost and time. This issue is directly related to the reliability of the elements, namely the subsystems that make up the system. This study examines the control architecture of speed governing system within the turbine control system of hydroelectric power plants, which has to be regarded as a critical system and provides an indispensable source of guidance and knowledge to researchers and also implementation engineers as well. For this perspective, a reliability analysis has been performed for the speed governing system and the risks with the control system have been revealed. Taking IEC 61508 and IEC 61511 standards as reference within this scope, the safety concepts and the related parameters have been explained and the corresponding methods for risk analysis have been mentioned. As a result, a new safety-related control system configuration overcoming the unacceptable risks with the speed governing system has also been proposed. It has been proved that safety integrity level of the proposed safety-related control system is at the desired level that can make the related safety related functions verify the identified safety level.

ENDIVIDAMENTO DE EMPRESAS CONCESSIONÁRIAS DE SANEAMENTO E ENERGIA ELÉTRICA NO BRASIL ENTRE 2004 E 2016

This paper aimed to identify the determinants of the Companies indebtedness at Electric and Sanitation sectors in Brazil. It was a quantitative and descriptive research, with secondary data took from the Base of The Best and Greatest of FIPECAFI. To compare the sectors indebtedness levels was used the Multiple Correspondence Analysis Method. The research population were the Sanitation and Electric Power Companies – public and private. The sample were the Electric Power and Sanitation utilities in Brazil, from 2004 to 2016. The results were estimated by Multiple Linear Regression with panel data. Were identifield correlations among the indebt utilities Companies and: (i) size; (ii)profitability; (iii)growth; (iv)tangibility; and (v) risk. Besides, the regulatory structure also showed its influence to the determination of the indebtedness of the Sanitation Companies.

Conceptual understanding of linear regression among economics students at the university center of Tipaza, Algeria

AbstractSolving problems related to econometrics requires a good knowledge of regression analysis concepts. The objective of this study is to evaluate students’ difficulties resulting from the lack of knowledge of regression analysis concepts among economics students enrolled in the Master’s cycle at the institute of economics at the university center of Tipaza (Algeria). In order to analyze students’ answers, a typical correction was prepared based on professors’ answers to this questionnaire. The procedure consists of comparing students’ key answers with their corresponding typical answers to see how near or far it is from the right answer. In order to see whether the difficulties are originated from the same students, we analyzed the association between answers based on Multiple Correspondence Analysis (MCA) method. The principal results showed that difficulties resulting from the lack of knowledge of regression analysis concepts were prevalent among students. Their main causes were strongly related to misunderstanding, misconceptions and confusions. MCA analysis indicated that students can be categorized according to their answers into four groups: a very weak group, a weak group, an average group and a good group. We concluded that the difficulty of solving problems in the context of linear regression among students is the result of a lack of knowledge of regression concepts coupled with the inability to explain them.