Hierarchical cluster classification and analysis of cirques in Slovenian Alps

Objective: A hierarchical cluster analysis for the cardboard manufacturing industry was developed with the aim of identifying similarities between workstations in terms of musculoskeletal stress factors (MSFs) and their impact on workers’ bodies.Methods: The hierarchical clustering analysis was conducted using data from 44 workstations, which included 6 body part divisions and 51 stress factors as variables with 36 answer options. Firstly, the content of the dataset was defined. Secondly, the data were agglomerated and classified into 3 clusters using Ward’s method based on the presence or absence of stress factors. Finally, the multivariable matrix was reduced to 2 factors: the x-axis representing the risk level of the workstation, and the y-axis representing the impact on the workers’ health.Results: The study found that workers’ knees were the most affected body parts, with 47 cases. The resulting work-related musculoskeletal disorders included tendinitis, arthralgia, chondromalacia, and gonarthrosis. The MSF with the most significant impact on the body’s health was fatiguing work that involves repeated jumps, prolonged squatting, or kneeling, present in cluster 1 and cluster 3. Moreover, two of the most common MSFs associated with repeated work positions were identified: a mild forward flexion of the back (63 cases) in combination with one leg being used more often to support the body (56 cases).Conclusions: It was possible to identify the main work-related musculoskeletal disorders and the associated stress factors for the cardboard manufacturing industry by using hierarchical cluster classification and analysis, enabling the classification of risk levels and the impact on body health for each workstation.

Applying hierarchical grey relation clustering analysis to geographical information systems – A case study of the hospitals in Taipei City

Hepatic Gene Expression Discriminates Responders and Nonresponders in Treatment of Chronic Hepatitis C Viral Infection

5241652 System for performing rule partitioning in a rete networkWilliam Barabash, William Yerazunis assigned to Digital Equipment Corporation

A chemometric approach coupled with capillary electrophoresis based on the hierarchical cluster analysis and principal component analysis has been applied for the investigation of the water quality in the Golcuk-Isparta region (Lake District of Turkey). In the research area, Egirdir Lake, Golcuk Lake and surrounding ground and domestic waters have been utilized as drinking water resources. Golcuk Lake is distinctive in terms of high fluoride content (3.50 ± 0.21 mg/mL) which is endemic in volcanic areas where the water flow through volcanic rocks and sediments. Based on the analysis of major anions chloride, sulfate, nitrate and fluoride with capillary electrophoresis, twenty-four drinking water sampling sites in the research area were classified into four classes using the hierarchical cluster and principal component analysis. Combining the research area investigation results of hierarchical cluster and principal component analysis, it was found that fluoride concentration is the major diagnostic variable to determine the quality of drinking waters, and all the other anions are the important classification factors to predict the resources of the drinking water samples, individually. To sum up, this study reveals the potential of the use of capillary electrophoresis in combination with chemometric techniques for the determination of the quality and origin of drinking waters.

The purpose of the present study was to investigate the differential impact of disease activity and severity on functional status and patient satisfaction in rheumatoid arthritis (RA) using cluster analysis on data from the FRANK registry. Data from 3,619 RA patients in the FRANK registry were analysed. Patients were grouped using hierarchical and k-means cluster analyses based on age, physician's global assessment (PhGA), patient's pain assessment (PtPA), and Steinbrocker stage. Clusters were evaluated for differences in functional status (mHAQ), quality of life (EQ5D), and patient satisfaction. Five distinct patient clusters were identified. In hierarchical cluster analysis, Cluster 1 (n=1195, 33.0%) and 2 (n=641, 17.7%) with lower disease activity and severity demonstrated better functional outcomes (mHAQ: 0.18±0.30 and 0.15±0.26, respectively) and higher satisfaction, with treatment efficacy scores of 1.9±0.7 and 2.0±0.7, respectively (1: very satisfied to 6: very unsatisfied). Cluster 3 (n=1117, 30.9%), characterised by less activity and more severity, showed significant joint damage (Steinbrocker stage III-IV: 95.4%) despite controlled inflammation. Cluster 4 (n=385, 10.6%), characterised by patient-physician discordance in disease activity (mean PhGA: 0.9±0.5; mean PtPA: 5.0±2.1), had a more pronounced negative effect on satisfaction. Cluster 5 (n=281, 7.8%), with more activity and moderate severity, had the poorest outcomes in functional status (mHAQ: 0.87±0.65), quality of life (EQ5D: 0.60±0.17), and satisfaction, with a treatment efficacy score of 2.9±0.9. k-Means clustering produced overall similar clusters to hierarchical clustering, allowing the same labels for Cluster 1 to Cluster 5. The study highlights the importance of understanding the heterogeneous nature of RA and its impact on patient outcomes. Personalised treatment approaches that address both objective disease measures and subjective patient experiences are essential for optimising RA management. Identification of distinct patient phenotypes, particularly those in Clusters 3, 4, and 5, may guide tailored interventions to improve treatment satisfaction and long-term outcomes in RA.

Business ethics is a set of rules by which individuals and institutions behave and conduct business in a responsible manner. It involves appropriate constraints on the pursuit of self-interest and profits, particularly when actions affect other stakeholders. Research on financial and other aspects of business ethics includes an examination of personal attitudes which give insight into ways in which people tend to behave as employees, managers, taxpayers and consumers. In this research, the standard ATBEQ questionnaire was extended with five variables covering corporate social responsibility and applied to a sample of business administration students in Croatia. The aim of the research was to identify groups of future managers based on an evaluation of their attitudes on business ethics and corporate social responsibility. The analysis was divided into two parts. In the first part, factor analysis was performed on 35 variables (attitudes) relating to business ethics and corporate social responsibility. Six factors were extracted and factor scores were calculated. In the second part, hierarchical and non-hierarchical cluster analyses were conducted. Factor scores were used as input data for the cluster analysis. Firstly, the hierarchical cluster analysis was run on the calculated factor scores. According to the dendrogram, a three-cluster solution was chosen. The non-hierarchical cluster analysis was then used to improve the results of the hierarchical cluster solution. Finally, these clusters (groups) of future managers were characterised according to their attitudes on financial and other aspects of business ethics and corporate social responsibility.

The hydrochemical evolution and flow pattern of groundwater is analyzed in a complex closed rift basin on the basis of multivariate hierarchical statistical cluster analysis. The analysis was made on the basis of water samples collected from over 120 wells and limited surface waters. The result revealed dissimilar hydrochemical phases in the rift and highlands representing different groundwater flow regimes. Five groundwater zones with different hydrochemical facies were identified. Both the conventional hydrochemical and multivariate statistical analyses indicate that the central sector of the rift represents a complex groundwater system influenced by thermal waters and alkaline lakes. It also demonstrates that the close similarity of lakes and groundwater with high fluoride, sodium, Total Dissolved Solids (TDS) and pH. The waters associated with acidic volcanic rocks are characterized by a positive alkalinity residual of calcite. When they concentrate due to the effect of climate, the precipitation of calcite causes a decrease in the chemical activity of calcium and increase in alkalinity. These waters become NaHCO3-dominated with distinctly different from highland systems characterized by Ca-MgHCO3 type waters with low TDS. Alkaline waters are intimately linked to acidic volcanics while fresh waters are associated with dominantly basic volcanics. Waters with similar hydrochemical facies as highland waters are evident in local fractures of the rift floor. The zonation of hydrochemical facies on the basis of hierarchical cluster analysis indicates increase in ionic concentration and pH along the groundwater flow path. Key words: Ethiopian rift, groundwater evolution, hierarchical cluster analysis, hydrochemistry, volcanic rocks.

Maintenance and repairing in actual engineering for long-term used structures, such as pipelines and bridges, make structural damage detection indispensable, as an unanticipated damage may give rise to a disaster, leading to huge economic loss. A new approach for detecting structural damage using transmissibility together with hierarchical clustering and similarity analysis is proposed in this study. Transmissibility is derived from the structural dynamic responses characterizing the structural state. First, for damage detection analysis, hierarchical clustering analysis is adopted to discriminate the damaged scenarios from an unsupervised perspective, taking transmissibility as feature for discriminating damaged patterns from undamaged ones. This is unlike directly predicting the structural damage from the indicators manifestation, as sometimes this can be vague due to the small difference between damaged scenarios and the intact baseline. For comparison reasons, cosine similarity measure and distance measure are also adopted to draw out sensitive indicators, and correspondingly, these indicators will manifest in recognizing damaged patterns from the intact baseline. Finally, for verification purposes, simulated results on a 10-floor structure and experimental tests on a free-free beam are undertaken to check the suitability of the raised approach. The results of both studies are indicative of a good performance in detecting damage that might suggest potential application in actual engineering real life.

Cluster analyses to explore the genetic curve pattern for milk yield of Holstein

This comparative analysis focuses on the interaction between the construction of the “political self” and the “moral self” and political behavior. The data derive from an online survey with a sample of 534 Greek citizens, employing symbolic representation and advanced multivariate methods, using hierarchical cluster analysis (HCA) and factorial correspondence analysis (FCA) in two steps. The analysis detects distinct profiles of respondents, based on their “democratic” and “moral” characteristics enabling us to uncover distinct discourses of political culture and behaviors. The first model reveals four groups of culture-behavior, characterized by the antagonisms between [mobilization–trust institutions–democracy as a struggle or parliamentary] and [apathy–reject institutions–democracy as ancient Greece, corruption, protest or direct]. The second model highlights the critical role of information sources, moral values, and political mobilization, revealing a typology on the poles: non-mobilization–naturalistic values, personal success, and enjoyment–tradition–passive information from television or social circle. The moral framework of values further outlined contrasts: progress versus preservation and aggression/power versus altruism/calmness. The two models offer a multidimensional interpretive framework for Greek political culture, structured around three principal axes: (1) institutional trust versus systemic suspicion; (2) collectivist solidarity versus individual self-interest; and (3) tradition-bound authority versus progress-based pluralism. Visualizing these discourses, internal antagonisms—differences and similarities in a two-dimensional semantic map—offer explicit insights into the Greek political landscape but also contribute to the broader field using HCA and FCA as a robust tool for comparative analysis.

Rheumatoid arthritis (RA) is one of the most prevalent chronic inflammatory and angiogenic diseases. The aim of this study was to evaluate the anti-inflammatory and anti-angiogenic activities in vitro of eight diterpenoids isolated from Daphne genkwa. LC-MS was used to identify diterpenes isolated from D. genkwa. The anti-inflammatory and anti-angiogenic activities of eight diterpenoids were evaluated on LPS-induced macrophage RAW264.7 cells and TNF-α-stimulated human umbilical vein endothelial cells (HUVECs) using hierarchical cluster analysis (HCA) and principal component analysis (PCA). The eight diterpenes isolated from D. genkwa were identified as yuanhuaphnin, isoyuanhuacine, 12-O-(2'E,4'E-decadienoyl)-4-hydroxyphorbol-13-acetyl, yuanhuagine, isoyuanhuadine, yuanhuadine, yuanhuaoate C and yuanhuacine. All the eight diterpenes significantly down-regulated the excessive secretion of TNF-α, IL-6, IL-1β and NO in LPS-induced RAW264.7 macrophages. However, only 12-O-(2'E,4'E-decadienoyl)-4-hydroxyphorbol-13-acetyl markedly reduced production of VEGF, MMP-3, ICAM and VCAM in TNF-α-stimulated HUVECs. HCA obtained 4 clusters, containing 12-O-(2'E,4'E-decadienoyl)-4-hydroxyphorbol-13-acetyl, isoyuanhuacine, isoyuanhuadine and five other compounds. PCA showed that the ranking of diterpenes sorted by efficacy from highest to lowest was 12-O-(2'E,4'E-decadienoyl)-4-hydroxyphorbol-13-acetyl, yuanhuaphnin, isoyuanhuacine, yuanhuacine, yuanhuaoate C, yuanhuagine, isoyuanhuadine, yuanhuadine. In conclusion, eight diterpenes isolated from D. genkwa showed different levels of activity in LPS-induced RAW264.7 cells and TNF-α-stimulated HUVECs. The comprehensive evaluation of activity by HCA and PCA indicated that of the eight diterpenes, 12-O-(2'E,4'E-decadienoyl)-4-hydroxyphorbol-13-acetyl was the best, and can be developed as a new drug for RA therapy.

A rapid ATR-FTIR spectroscopic method for detection of sibutramine adulteration in tea and coffee based on hierarchical cluster and principal component analyses.

Cluster analysis refers to a class of data reduction methods used for sorting cases, observations, or variables of a given dataset into homogeneous groups that differ from each other. The present paper focuses on hierarchical agglomerative cluster analysis, a statistical technique where groups are sequentially created by systematically merging similar clusters together, as dictated by the distance and linkage measures chosen by the researcher. Specific distance and linkage measures are reviewed, including a discussion of how these choices can influence the clustering process by comparing three common linkage measures (single linkage, complete linkage, average linkage). The tutorial guides researchers in performing a hierarchical cluster analysis using the SPSS statistical software. Through an example, we demonstrate how cluster analysis can be used to detect meaningful subgroups in a sample of bilinguals by examining various language variables.

Hierarchical clustering and compositional data analysis for interpreting groundwater hydrogeochemistry: The application to Campi Flegrei volcanic aquifer (south Italy)