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Journal articles on the topic 'Advanced Cluster Analysis'

Author: Grafiati

Published: 27 July 2024

Last updated: 31 July 2025

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1

Feng, Guohuan, Junchen Lin, and Keyi Wang. "Researches Advanced in Clustering Algorithms." Highlights in Science, Engineering and Technology 16 (November 10, 2022): 168–77. http://dx.doi.org/10.54097/hset.v16i.2498.

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Clustering is a technique to find the intrinsic structure between data and is a fundamental problem in many data-driven application fields. Currently, clustering is generally modeled as an unsupervised learning task, aiming to mine similar features between different samples and cluster samples with similar features into clusters. Ideally, objects in the same cluster are expected to be similar in the clustering results, while objects in different clusters are quite different. This study summarizes the research status of clustering algorithms in recent years. Specifically, the relevant critical

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DAGIM, S., E. V. PUSTOVALOV, A. N. FEDORETS, and A. M. FROLOV. "EXPLORING AMORPHOUS ALLOYS: ADVANCED ELECTRON MICROSCOPY AND CLUSTER ANALYSIS." Computational nanotechnology 11, no. 1 (2024): 112–20. http://dx.doi.org/10.33693/2313-223x-2024-11-1-112-120.

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In this study, we explored the atomic structure and orderliness of amorphous alloys through advanced electron microscopy and analytical techniques. Amorphous alloys, characterized by disordered atomic structures, exhibit promising applications in technology. The research addresses a crucial knowledge gap by investigating cluster distribution, particle arrangement, and orderliness within the amorphous matrix. High-resolution electron microscopy (HREM) images are analyzed using diverse algorithms and software tools. The study establishes a correlation between angles approaching 180 degrees and i

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Yadav, Pradeep Kumar, R. S. Sikarwar, Badal Verma, Sushma Tiwari, and D. K. Shrivastava. "Genetic Divergence for Grain Yield and Its Components in Bread Wheat (Triticum aestivum L.): Experimental Investigation." International Journal of Environment and Climate Change 13, no. 5 (2023): 340–48. http://dx.doi.org/10.9734/ijecc/2023/v13i51776.

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The present investigation Comprises 34 advanced breeding lines including checks of bread wheat and experiment was conducted in a complete randomized block design with three replications at the research farm department of genetics and plant breeding, RVSKVV, B.M. College of Agriculture, Khandwa during Rabi season (November 2021 to April 2022) for estimation of the multivariate analysis of divergence. The advanced breeding lines were grouped into seven clusters. Cluster III contained the highest number of advanced breeding lines(12) and clusters V, VI, and VII contained the lowest (1 each). The

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Ochilov, Ilhom. "Improvement of financial analysis of cluster activities." BIO Web of Conferences 140 (2024): 06007. http://dx.doi.org/10.1051/bioconf/202414006007.

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This research paper addresses the critical need for an advanced framework to elevate the financial analysis of cluster activities. Clusters, defined as geographically proximate groups of interconnected companies and associated institutions in a particular field, have emerged as key drivers of economic growth. However, the existing financial analysis methods often fall short in capturing the complex dynamics and interdependencies within these clusters. The paper delves into the current challenges and limitations of conventional financial analysis in the context of cluster activities. It highlig

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Siddika, A., A. K. M. Aminul Islam, M. G. Rasul, M. A. K. Mian, and J. U. Ahmed. "GENETIC DIVERSITY IN ADVANCED GENERATION OF VEGETABLE PEA (Pisum sativum L.)." Bangladesh Journal of Plant Breeding and Genetics 27, no. 1 (2015): 9–16. http://dx.doi.org/10.3329/bjpbg.v27i1.23972.

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Twenty five advanced lines among them twelve lines obtained from the cross between Edible Podded Pea and IPSA Motorsuty-1, nine obtained from the cross between Local White and IPSA Motorsuty-3 and five parental lines were included to measure genetic diversity. The field experiment was conducted at the research farm, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh. Analysis of variance showed significant differences among the genotypes for all characters. Multivariate analysis based 14 agronomic characters indicated that the 26 genotypes fell into five distant clu

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Streur, Megan, Sarah J. Ratcliffe, David Callans, M. Benjamin Shoemaker, and Barbara Riegel. "Atrial fibrillation symptom clusters and associated clinical characteristics and outcomes: A cross-sectional secondary data analysis." European Journal of Cardiovascular Nursing 17, no. 8 (2018): 707–16. http://dx.doi.org/10.1177/1474515118778445.

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Background: Symptom clusters among adults with atrial fibrillation have previously been identified but no study has examined the relationship between symptom clusters and outcomes. Aims: The purpose of this study was to identify atrial fibrillation-specific symptom clusters, characterize individuals with each cluster, and determine whether symptom cluster membership is associated with healthcare utilization. Methods: This was a cross-sectional secondary data analysis of 1501 adults from the Vanderbilt Atrial Fibrillation Registry with verified atrial fibrillation. Self-reported symptoms were m

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Sánchez, José Luis Ausejo, Patricia Elena Ramos La Rosa, Damaris Faviola Medina Palma, Gleny Amelia Ching Campos, and Yolanda Emperatriz Maguiña Poma. "What topics are investigated in circular economy research? A co-word analysis using hierarchical clustering." Iberoamerican Journal of Science Measurement and Communication 5, no. 1 (2025): 1–11. https://doi.org/10.47909/ijsmc.1623.

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Objective. We analyzed the most researched topics related to the circular economy. To this end, we used a bibliometric approach, generating thematic maps that group the most used terms in the scientific literature. Design/Methodology/Approach. The present study focused on hierarchical clustering analysis to identify and understand interrelated themes in circular economy research. Adopting Ward's method, the analysis was performed without predetermining the number of groups. The data set was extracted from the Scopus database. Author keywords and keywords plus were used for the study. Results/D

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Dalcin, Thais, Alsones Balestrin, and Eduardo Künzel Teixeira. "Start-Up Cluster Development: A Multi-Case Analysis in the Brazilian Context." International Journal of Innovation and Technology Management 14, no. 06 (2017): 1750035. http://dx.doi.org/10.1142/s0219877017500353.

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This paper aims to contribute to knowledge on start-up cluster development by describing the core resource configurations in the development trajectory of start-up clusters in an emergent country. This research involves two start-up clusters in the Brazilian context. The results provide a framework formed by four stages that indicates the trajectory of start-up cluster development from the basic level, in which the most evident resources are tangible and endogenous, to the more advanced level, which comprises intangible and exogenous resources. In the fourth stage, start-up clusters improve re

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Randler, Christoph. "An Analysis of Heterogeneity in German Speaking Birdwatchers Reveals Three Distinct Clusters and Gender Differences." Birds 2, no. 3 (2021): 250–60. http://dx.doi.org/10.3390/birds2030018.

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The purpose of this study was to segment birdwatchers into clusters. Members from a wide range of bird related organizations, from highly specialized birders as well as Facebook bird group members were studied to provide a diverse dataset (n = 2766; 50.5% men). Birding specialization was measured with a battery of questionnaires. Birding specialization encompassed the three constructs of skill/competence, behavior, personal and behavioral commitment. Additionally, involvement, measured by centrality to lifestyle, attraction, social bonding, and identity, was used. The NbClust analyses showed t

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Meijer, Ilse, Marc M. Terpstra, Oscar Camara, Henk A. Marquering, Nerea Arrarte Terreros, and Joris R. de Groot. "Unsupervised Clustering of Patients Undergoing Thoracoscopic Ablation Identifies Relevant Phenotypes for Advanced Atrial Fibrillation." Diagnostics 15, no. 10 (2025): 1269. https://doi.org/10.3390/diagnostics15101269.

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Background/Objectives: The rate of recurrence after ablation for atrial fibrillation (AF) is considerable. Risk stratification for AF recurrence after ablation remains incompletely developed. Unsupervised clustering is a machine learning technique which might provide valuable insights in AF recurrence by identifying patient clusters using numerous clinical characteristics. We hypothesize that unsupervised clustering identifies patient clusters with different clinical phenotypes, including AF type and cardiovascular morbidities, and ablation outcomes. Methods: Baseline and procedural characteri

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Bates, Ian, Sherly Meilianti, Lina Bader, Rishi Gandhi, Rachael Leng, and Kirsten Galbraith. "Strengthening Primary Healthcare through accelerated advancement of the global pharmacy workforce: a cross-sectional survey of 88 countries." BMJ Open 12, no. 5 (2022): e061860. http://dx.doi.org/10.1136/bmjopen-2022-061860.

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ObjectiveAdvancing the pharmacy workforce contributes to strengthening primary healthcare and accelerating progress towards universal health coverage. This study aimed to identify key enablers to support policy development for national pharmacy workforce advancement.DesignA cross-sectional country-level questionnaire was distributed from July 2018 to March 2019.SettingNational-level or country-level pharmacy workforce development policy.ParticipantsProfessional leadership associations and national agencies of the International Pharmaceutical Federation (FIP). The FIP global database included 1

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Pahuja, Anjali K., Kundan Singh Chufal, Irfan Ahmad, et al. "Identifying Prognostic Groups Using Machine Learning Tools in Patients Undergoing Chemoradiation for Inoperable Locally Advanced Nonsmall Cell Lung Carcinoma." Asian Journal of Oncology 05, no. 02 (2019): 056–63. http://dx.doi.org/10.1055/s-0039-3401437.

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Abstract Introduction Unresectable stage III nonsmall cell lung cancer (NSCLC) continues to have dismal 5-year overall survival (OS) rate. However, a subset of the patients treated with chemoradiation show significantly better outcome. Prediction of treatment outcome can be improved by utilizing machine learning tools, such as cluster analysis (CA), and is capable of identifying complex interactions among many variables. We have utilized CA to identify a cluster with good prognosis within stage III NSCLC. Materials and Methods Retrospective analysis of treatment outcomes was done for 92 patien

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Yennu, Sriram, Janet L. Williams, Gary B. Chisholm, and Eduardo Bruera. "The effects of dexamethasone and placebo on symptom clusters in advanced cancer patients: A preliminary report." Journal of Clinical Oncology 33, no. 29_suppl (2015): 187. http://dx.doi.org/10.1200/jco.2015.33.29_suppl.187.

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187 Background: Advanced cancer patients frequently experience debilitating symptoms that occur in clusters, but few pharmacological studies have targeted symptom clusters. Our objective was to examine the effects of dexamethasone on symptom clusters. Methods: Secondary analysis of a recent RCT of dexamethasone (DEX) vs placebo (PL) on cancer symptoms as assessed by FACIT-F-Fatigue; FAACT-Anorexia-Cachexia; BPI - Pain; HADS- Anxiety-Depression; ESAS: Sleep, Drowsiness, Dyspnea. Symptom clusters were identified based on baseline symptoms [ESAS] using principal component analysis. Cluster scores

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Tolasa, Diriba. "Advancements in Molecular and Cluster Physics: Challenges and Innovations." Nanoscience and Nanometrology 9, no. 1 (2025): 1–10. https://doi.org/10.11648/j.nsnm.20250901.11.

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Molecular and cluster physics is an interdisciplinary field that explores the properties and interactions of small groups of atoms and molecules, providing critical insights into the behavior of matter at the Nano scale. Recent advancements in experimental techniques, theoretical models, and computational methods have significantly enhanced our understanding of molecular dynamics and cluster formation. This paper reviews these innovations, highlighting key developments in spectroscopy, microscopy, and mass spectrometry that have revolutionized the characterization of molecular systems. Techniq

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Pryadko, S. N., and S. A. Kucheryavenko. "Knowledge-Intensive Market: Geomarketing and Cluster Approach to Functioning and Analysis." Proceedings of the Southwest State University. Series: Economics. Sociology. Management 13, no. 5 (2023): 128–40. http://dx.doi.org/10.21869/2223-1552-2023-13-5-128-140.

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Relevance. Innovative development is one of the highest priority tasks of the economy at the national and regional level. One of the directions for solving these problems is the formation of local knowledge-intensive markets, within which the interaction of the main participants in the innovation cycle takes place - from conducting fundamental scientific research to introducing a knowledge-intensive product to the market. The object of the study was the local knowledge-intensive market of the Belgorod region. The sources of information for the study were data from the World Intellectual Proper

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P. B., Revanth, Lakshmana D., Manjunatha B., Rajashekharappa K., and Mallikarjuna H B. "Genetic Variability Studies in Dolichos Bean (Lablab purpureus L.) for Yield and Yield Traits." Journal of Advances in Biology & Biotechnology 27, no. 11 (2024): 926–31. http://dx.doi.org/10.9734/jabb/2024/v27i111676.

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Aims: To study the genetic variability by phenotypic coefficient of variation, genotypic coefficient of variation, heritability and genetic advance as percent of mean in advanced breeding lines of Dolichos bean. Study Design: Augmented RCBD with six blocks. Place and Duration of Study: Department of Genetics and Plant Breeding, College of Agriculture, Shivamogga, during Late Kharif 2023. Methodology: The experimental material consisted of 64 advanced breeding lines of Dolichos bean including four checks viz., Hebbal avere-1, Hebbal avere-3, Hebbal avere-4 and Arka Jaya. Results: Analysis of va

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Molina-García, Manuel, María Jesús Rojas-Lechuga, Teresa Torres Moral, et al. "Integrative Molecular and Immune Profiling in Advanced Unresectable Melanoma: Tumor Microenvironment and Peripheral PD-1+ CD4+ Effector Memory T-Cells as Potential Markers of Response to Immune Checkpoint Inhibitor Therapy." Cancers 17, no. 12 (2025): 2022. https://doi.org/10.3390/cancers17122022.

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Background/Objectives: Immune checkpoint inhibitors (ICIs) have revolutionized advanced melanoma treatment, yet many patients fail to achieve sustained clinical benefit. Several biomarkers, including tumor microenvironment (TME) signature, PD-1/PD-L1 expression, and IFN-γ signaling, have been proposed. However, robust predictive markers remain elusive. This study aimed to identify molecular markers of response by analyzing tumor and peripheral immune signatures. Methods: This study analyzed 21 advanced melanoma patients treated with ICIs. Formalin-fixed, paraffin-embedded tumors underwent RNA-

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GAMIDULLAEVA, Leila A., and Dmitrii N. SHEVCHENKO. "Cluster approach potential in the progress of the territory of advanced social and economic development." National Interests: Priorities and Security 21, no. 1 (2025): 84–93. https://doi.org/10.24891/ni.21.1.84.

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Subject. The article discusses the problem of clustering the economy, formation of growth points. Objectives. The study aims to underpin the advantages of cluster approach to realizing the potential of territories of advanced socioeconomic development. Methods. The study employs methods of logical and statistical analysis. Results. The cluster policy to support territories of advanced social and economic development demonstrates its effectiveness. We developed recommendations for the creation of economic clusters in the Penza Oblast. Conclusions. The findings can be used to devise measures to

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Christy A., Joy. "An advanced ilrcpsd technique for bridging the competency and cognitive skills of students in higher education." International Journal of Engineering & Technology 7, no. 1.3 (2017): 37. http://dx.doi.org/10.14419/ijet.v7i1.3.8984.

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Data mining refers to the extraction of meaningful knowledge from large data sources as it may contain hidden potential facts. In general the analysis of data mining can either be predictive or descriptive. Predictive analysis of data mining interprets the inference of the existing results so as to identify the future outputs and the descriptive analysis of data mining interprets the intrinsic characteristics or nature of the data. Clustering is one of the descriptive analysis techniques of data mining which groups the objects of similar types in such a way that objects in a cluster are closer

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Zhang, Zhimin, Dezhi Han, Songyang Wu, Wenqi Sun, and Shuxin Shi. "Identification and detection of illegal gambling websites and analysis of user behavior." Computer Science and Information Systems, no. 00 (2025): 19. https://doi.org/10.2298/csis240930019z.

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Illegal gambling websites use advanced technology to evade regulations, posing cybersecurity challenges. To address this, we propose a machine learning method to identify these sites and analyze user behavior accurately. The method extracts key data from post messages in a real-world network environment, generating word vectors via Word2Vec with TF-IDF, which are then downscaled and feature-extracted using a Stacked Denoising Auto Encoder (SDAE). Next, this paper uses Agglomerative Clustering, improved through a combination of distance caching and heap optimization, to initially cluster post-t

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Kolisnichenko, Natalya. "Advantages of clusters in Ukraine’s recovery." Socio-Economic Problems and the State 31, no. 2 (2024): 3–10. https://doi.org/10.33108/sepd2024.02.003.

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The paper examines the advantages of clusters in Ukraine’s recovery by studying their characteristics and innovative nature. Factual and analytical material was developed using logical- factual, comparative methods and systematic analysis. It clarifies the definition of a cluster and investigates the features of state cluster policy and cluster management. It a revealed that today, clusters play the role of drivers in Ukraine’s recovery by supporting creative technologies, critical infrastructure, and other progressive changes. A SWOT analysis of the directions in the development and implement

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Ringer, Simon P. "Advanced Nanostructural Analysis of Aluminium Alloys Using Atom Probe Tomography." Materials Science Forum 519-521 (July 2006): 25–34. http://dx.doi.org/10.4028/www.scientific.net/msf.519-521.25.

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This paper sets out the needs for and recent advances in microscopy in Al alloys, using solutesolute and solute-vacancy clustering as examples. Cluster-assisted nucleation and cluster strengthening are discussed and this is followed by a discussion of the local electrode atom probe. Heuristic and algorithmic tools for assessing the nanoscale microstructure or nanostructure of Al alloys acquired from atom probe tomography experiments are then presented.

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Aktas, Aynur, Declan Walsh, Lisa A. Rybicki, and Anne Fitz. "Symptom clusters and demographic characteristics in advanced cancer." Journal of Clinical Oncology 31, no. 15_suppl (2013): 9638. http://dx.doi.org/10.1200/jco.2013.31.15_suppl.9638.

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9638 Background: Little is known about demographic variations in cancer symptom clusters (SC). Our objective was to determine whether SC are associated with age, gender, race, performance status (PS), or primary cancer site. Methods: Symptoms from 1000 advanced cancer patients referred to a palliative medicine program were recorded prospectively. Among 922 patients with complete symptom data, hierarchical cluster analysis identified 7 SC. A SC was considered present if the patient had ≥50% of the symptoms in the cluster. Comparisons were made between patients with and without each cluster usin

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Lee, You Won, Eun Ji Lee, Seung Yeon Oh, et al. "Abstract 5935: Phenotype profiling of tumor microenvironment in EGFR mutant lung adenocarcinoma with multi-omics data." Cancer Research 83, no. 7_Supplement (2023): 5935. http://dx.doi.org/10.1158/1538-7445.am2023-5935.

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Abstract Introduction: EGFR mutations holds the major targets for drug in lung adenocarcinoma (LUAD). Despite the tremendous study of EGFR mutant (MT) LUAD, the comprehensive interpretation of the heterogeneous character of LUAD harboring EGFR MT remains a key challenge. Here, we investigated the heterogeneity of EGFR MT LUAD and explored the tumor microenvironment (TME) in EGFR MT LUAD. Method: We performed single-cell RNA sequencing (scRNA-seq) from 135 LUAD patients which consist of normal(n=24), EGFR wild (WT)(n=18), and MT(n=93). Also, we used whole genome sequencing and bulk-RNA sequenci

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Pahria, Tuti, Yuliana Yuliana, Atlastieka Praptiwi, Maha Atout, and Hana Rizmadewi Agustina. "Symptom Clusters and Quality of Life among Women Living with Cancer." Jurnal Keperawatan Soedirman 18, no. 3 (2023): 129. http://dx.doi.org/10.20884/1.jks.2023.18.3.8530.

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The prevalence of cancer in Indonesia has increased and is one of the biggest causes of death. Symptom clusters, a collection of symptoms in cancer patients that appear together and are related to one another, can affect the quality of life of cancer patients. This study aims to identify the relationship between symptom clusters and the quality of life of advanced cancer patients. This research used cross-sectional quantitative survey data from a cancer patient care unit at a referral hospital in West Java Province with a total of 140 respondents. Consecutive sampling was conducted for three m

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Jagadeesh, Kommineni, Mahto C. S., Niraj Kumar, and Lal H. C. "Genetic diversity and character association studies for agro-morphological and quality traits of advanced breeding lines in field pea (Pisum sativum L.)." Electronic Journal of Plant Breeding 15, no. 4 (2024): 912–20. https://doi.org/10.37992/2024.1504.098.

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Abstract The present study analysed the trait associations and the genetic diversity for morphological and qualitative traits among the 23 field pea genotypes using multivariate analysis. The correlation analysis revealed that traits like primary branches per plant, pod length, seeds per pod, harvest index and biological seed yield per plant showed a note-worthy positive association at both genotypic and phenotypic levels. Path analysis revealed the correlation of pod length, harvest index and biological yield per plant was due to direct positive effects. The principal component analysis indic

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Purwaningrum, Alfi, Amalia Nur Alifah, Dwi Bagus Dermawan, and Galuh Andini. "Unlocking Pharma Market Segmentation for Strategic Growth Through Advanced Data Intelligence." Engineering, MAthematics and Computer Science Journal (EMACS) 7, no. 1 (2025): 25–34. https://doi.org/10.21512/emacsjournal.v7i1.12199.

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Business competition compels companies to understand customer characteristics in order to maintain and enhance their competitiveness, especially in the pharmaceutical industry, which involves various customer segments such as hospitals, pharmacies, patients, and end consumers with diverse needs. Customer segmentation becomes crucial in developing effective strategies, with K-Means algorithm being one of the commonly used methods due to its simplicity and efficiency in clustering large datasets. This study combines the K-Means Clustering algorithm with the elbow method to determine the optimal

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Shukla, Balraj R., and Anup K. Panda. "A Novel Classification System of Smart Mechanical Plaque Control: A Cross-Sectional Survey with Cluster Analysis." Indian Journal of Community Medicine 50, no. 1 (2025): 175–80. https://doi.org/10.4103/ijcm.ijcm_439_23.

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Background: Recurring advances in the field of mechanical plaque control (MPC) devices have shown promise in improving the oral hygiene status of the community. However, little is known about the association between the knowledge of healthcare professionals regarding these advances, the manufacturers in understanding the demand of the community, and the community’s willingness to switch to these “smarter” advances in MPC. This article puts forth a novel classification system of smart MPC to bridge this research gap. Materials and Methods: After a Delphi consensus and a sample pretesting, a cus

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Vahldiek, Kai, and Frank Klawonn. "Cluster-Centered Visualization Techniques for Fuzzy Clustering Results to Judge Single Clusters." Applied Sciences 14, no. 3 (2024): 1102. http://dx.doi.org/10.3390/app14031102.

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Fuzzy clustering, as a powerful method for pattern recognition and data analysis, often produces complex results that require careful examination of individual clusters. In this paper, advanced visualization techniques are presented that aim to facilitate the analysis of fuzzy clustering results by focusing on the evaluation and interpretation of individual clusters. The presented approach is based on the development of cluster-centric visualization techniques that consider the inherent uncertainty of fuzzy clustering results. The novelty is an assessment of individual clusters with the propos

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Artemenko, Andriy. "ANALYSIS OF THE CURRENT STATE OF CLUSTER DEVELOPMENT IN THE REGIONS OF UKRAINE AND THE WORLD." Green, Blue and Digital Economy Journal 5, no. 3 (2024): 1–5. https://doi.org/10.30525/2661-5169/2024-3-1.

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The cluster approach has become a pivotal model for fostering regional development worldwide, contributing significantly to economic competitiveness, innovation potential, and efficient resource management. This study analyzes the current state of cluster development in Ukraine and compares it with global trends. It highlights the role of clusters in addressing regional economic challenges and improving integration into global markets. Despite its potential, Ukraine faces numerous obstacles in cluster formation, including insufficient funding, weak infrastructure, and a lack of collaboration a

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Lee, Sehee, and Yoonsun Lee. "A Comparative Analysis of Clustering Algorithms for Assessing College Students’ Key Competencies." Korean Society for Educational Evaluation 37, no. 3 (2024): 411–39. http://dx.doi.org/10.31158/jeev.2024.37.3.411.

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The purpose of this study was to categorize students into distinct groups based on their key competency development levels. For this purpose, four clustering algorithms - Agglomerative hierarchical clustering, k-means clustering, Gaussian mixture model clustering, and DBSCAN - were utilized with data collected from 434 students at a university in Seoul. Agglomerative hierarchical clustering revealed two clusters, with one group showing higher development levels across all key competencies and the other exhibiting competencies below the average. Similarly, k-means clustering identified an optim

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Sharmila, Kuna, Deepak Gauraha, Abhinav Sao, Sagi Indumathi, and Dharavath Nagaraju. "Exploring Genetic Variability and Diversity in Advanced Breeding Lines of Rice for Yield-Attributing and Grain Quality Traits." Journal of Advances in Biology & Biotechnology 28, no. 4 (2025): 42–56. https://doi.org/10.9734/jabb/2025/v28i42167.

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Genetic variability and diversity are crucial for enhancing yield and grain quality in rice (Oryza sativa L.). A field experiment was conducted during Kharif, 2023 at the Research cum Instructional Farm, Department of Genetics and Plant Breeding, College of Agriculture, IGKV, Raipur (C.G.). Thirty-three advanced breeding lines were evaluated for 30 yield-attributing and grain quality traits using a Randomized Block Design (RBD) with two replications. Analysis of variance revealed highly significant differences among the lines, indicating substantial genetic variability. Genetic parameter evalu

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Campregher, Paulo V., Santosh K. Srivastava, Nobuharu Fujii, H. Joachim Deeg, Harlan S. Robins та Edus Warren. "Analysis of the αβ T Cell Receptor Repertoire in Advanced Myelodysplastic Syndrome". Blood 112, № 11 (2008): 3650. http://dx.doi.org/10.1182/blood.v112.11.3650.3650.

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Abstract Analysis of the αβ T cell receptor (TCR) repertoire in patients with myelodysplastic syndrome (MDS) using the technique of TCR β chain spectratyping has provided valuable insights into the pathophysiology of cytopenias in a subset of patients. TCR β chain spectratypes represent complex datasets, however, and statistical tools for their comprehensive analysis are limited. To enable global comparison of spectratype data from different individuals, we developed a robust statistical method based on k-means clustering analysis, and applied this method to analysis of the αβ TCR repertoires

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Paoloni, Francesco, Federica Pecci, Giulia Bruschi, et al. "Pan-cancer G2C-Pro: A two-stage Gaussian clustering to prognostically stratify patients with advanced tumors treated with immune checkpoint inhibitors." Journal of Clinical Oncology 42, no. 16_suppl (2024): e13605-e13605. http://dx.doi.org/10.1200/jco.2024.42.16_suppl.e13605.

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e13605 Background: Immune checkpoint inhibitors (ICIs) have revamped the clinical outcomes of patients (pts) affected by advanced solid tumors. The aim of our study is to develop a two-stage Gaussian Clustering algorithm (G2C) integrated with a logistic regression model (Pro) to prognostically stratifypts with advanced solid tumors treated with ICIs (pan-cancer G2C-Pro) based on baseline features. Methods: Data extraction involved, retrospectively, pts with advanced solid tumors (lung, melanoma, renal cancer, head and neck, urothelial carcinoma) treated with ICIs at Department of Medical Oncol

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Nuruzzaman, Md, Md Shohel Rana, Aleya Ferdausi, Md Monjurul Huda, Lutful Hassan, and Shamsun Nahar Begum. "Clustering and Principal Component Analysis of Nerica Mutant Rice Lines Growing Under Rainfed Condition." International Journal of Applied Sciences and Biotechnology 7, no. 3 (2019): 327–34. http://dx.doi.org/10.3126/ijasbt.v7i3.25703.

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A field experiment was conducted at subtropical region in Bangladesh to assess the contribution of morphological traits to variability in some NERICA mutant rice lines. The experiment was conducted following RCBD with three replications. Thirty-one NERICA rice genotypes (twenty-eight mutant lines along with three parents) of advanced generations were used. Data were collected on twelve morphological traits. The results of the principal component analysis showed that the first four components account for 80% of total variation giving a clear idea of the structure underlying the variables analyz

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Sharma, Abhinav, Yinggan Zheng, Justin A. Ezekowitz, et al. "Cluster Analysis of Cardiovascular Phenotypes in Patients With Type 2 Diabetes and Established Atherosclerotic Cardiovascular Disease: A Potential Approach to Precision Medicine." Diabetes Care 45, no. 1 (2021): 204–12. http://dx.doi.org/10.2337/dc20-2806.

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OBJECTIVE Phenotypic heterogeneity among patients with type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease (ASCVD) is ill defined. We used cluster analysis machine-learning algorithms to identify phenotypes among trial participants with T2DM and ASCVD. RESEARCH DESIGN AND METHODS We used data from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS) study (n = 14,671), a cardiovascular outcome safety trial comparing sitagliptin with placebo in patients with T2DM and ASCVD (median follow-up 3.0 years). Cluster analysis using 40 baseline variables was cond

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Prabaswara, Ireneus, Dwika Ananda Agustina Pertiwi, and Jumanto Jumanto. "Analysis of k-means clustering algorithm in advanced country clustering using rapid miner." Journal of Student Research Exploration 2, no. 2 (2024): 101–10. http://dx.doi.org/10.52465/josre.v2i2.337.

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In the era of globalization, the understanding of developed countries is no longer limited to the level of per capita income alone. As part of the analysis of developed countries based on aspects of government revenue, income balance, national savings, and domestic output based on sales. This research aims to cluster and to find out how these economic indicators are interrelated and affect the status of a country as a developed country. The K-means algorithm is used to identify patterns of countries with similar economic characteristics. From the research conducted, there are 4 clusters genera

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Mayvani, Titov Chuk's, Rifai Afin, Alifah Rokhmah Idialis, and Sariyani Sariyani. "Analysis of Growth and Tourism Clusters in Madura." Jurnal Ekonomi dan Studi Pembangunan 14, no. 1 (2022): 59. http://dx.doi.org/10.17977/um002v14i12022p059.

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The tourism sector is one of the essential sectors that drive economic growth. There are many tourist destinations in Madura Island that have uniqueness, where the tourism is based on beaches, culture, history, and even religion. However, the existence of tourist destinations has not been widely felt by the Madurese community economically. Therefore, tourism development in Madura needs attention, considering the tourism sector plays a vital role in encouraging economic growth. This research uses scalogram analysis and K-Means Clustering analysis. The scalogram analysis consists of Location Coe

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Nasir, Umar, Haseeb Ahmad, Sahibzadi Fatima Tariq, Mahwish zeb, Fiza Shafiq, and Asfandyar Qureshi. "An Investigation to Assess Occlusal and Psychological Parameters in Bruxism." Pakistan Journal of Medical and Health Sciences 16, no. 2 (2022): 145–47. http://dx.doi.org/10.53350/pjmhs22162145.

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Aim: To assess the anxiety and occlusal features in bruxism by means of T-Scan III and Hospital Anxiety and Depression Scale correspondingly. Study design: Case control study Place and duration of study: Department of Oral Medicine, Khyber Medical University-Institute of Dental Sciences, Kohat from 1st December 2020 to 30th November 2021. Methodology: This study comprised of a cluster of fifty patients with bruxism (Cluster Bxm) and fifty healthy persons as control cluster (Cluster NBxm). Patients were nominated from outdoor patients coming to Private Dental Teaching Hospital in Peshawar with

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Singha, Tanoy, Md Asif Mahamud, Shahin Imran, et al. "Genetic diversity analysis of advanced rice lines for salt tolerance using SSR markers." Asian Journal of Medical and Biological Research 7, no. 2 (2021): 214–21. http://dx.doi.org/10.3329/ajmbr.v7i2.55001.

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Twenty-two rice lines were used to evaluate salt tolerance at the Laboratory of Biotechnology Division of Bangladesh Institute of Nuclear Agriculture (BINA), Mymensingh. Four SSR markers viz. AP3206f, RM1287, RM7075, and RM10793 were used to screen the germplasm for salt tolerance. SSR analysis revealed that the number of alleles per locus ranged from 3 to 5 with an average of 4.25 alleles per locus. Polymorphism Information Content (PIC) values ranged from 0.4762 (RM7075) to 0.7524 (AP3206f) with an average of 0.61 per locus. The highest genetic diversity (0.7810) was observed in loci AP3206f

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Pachauri, Atul Kumar, Deepak Gauraha, Sant Ram Sahu, Praveen Pujari, and Deepak Saran. "Molecular Diversity and Population Structure Analysis in Rice Genotype using SSR Markers." Environment and Ecology 41, no. 3C (2023): 1883–90. http://dx.doi.org/10.60151/envec/jwhx9999.

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The use of advanced molecular technologies is one possible approach to understand their diversity. A study was undertaken to evaluate forty two rice genotype including six checks during kharif 2019. The result of the investigation was allele number was recorded for the five markers with an average of 2.6 allele per locus. Out of twenty five markers 12 markers showed highly PIC value. However, UPGMA cluster diagram mean of 67% level of similarity showed forty two accessions into 10 distinct clusters. Maximum cluster II had 13 genotypes followed by cluster IV, X, III and IX consisting of eleven,

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JAVED, A., N. N. NAWAB, S. GOHAR, et al. "GENETIC ANALYSIS AND HETEROTIC STUDIES IN TOMATO (SOLANUM LYCOPERSICUM L.) HYBRIDS FOR FRUIT YIELD AND ITS RELATED TRAITS." SABRAO Journal of Breeding and Genetics 54, no. 3 (2022): 492–501. http://dx.doi.org/10.54910/sabrao2022.54.3.3.

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A study was conducted to determine the types of gene action of different yield-related traits in tomato and the combining ability in four advanced lines. The heterotic response in tomato hybrids was also assessed. Analysis of variance (ANOVA) revealed significant differences (P ≤ 0.05) among all the traits. General combining ability (GCA) and specific combining ability (SCA) for all chosen traits were computed using Griffing’s approach of diallel. Combining ability revealed the additive and non-additive genetic effects for all selected traits of advanced lines. T-1360 was found as a good gener

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Zhou, Jian, Alexandra Vorobyeva, Qiyue Luan, and Ian Papautsky. "Single Cell Analysis of Inertial Migration by Circulating Tumor Cells and Clusters." Micromachines 14, no. 4 (2023): 787. http://dx.doi.org/10.3390/mi14040787.

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Single-cell analysis provides a wealth of information regarding the molecular landscape of the tumor cells responding to extracellular stimulations, which has greatly advanced the research in cancer biology. In this work, we adapt such a concept for the analysis of inertial migration of cells and clusters, which is promising for cancer liquid biopsy, by isolation and detection of circulating tumor cells (CTCs) and CTC clusters. Using high-speed camera tracking live individual tumor cells and cell clusters, the behavior of inertial migration was profiled in unprecedented detail. We found that i

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., Naresh, Mohinder Singh Dalal, Lalit Kumar, Suman Devi, Amit ., and Rukoo Chawla. "Assessment of genetic diversity for heat tolerance in advanced breeding lines of bread wheat (Triticum aestivum L. em.Thell.)." Environment and Ecology 41, no. 4B (2023): 2679–87. http://dx.doi.org/10.60151/envec/mcsm4521.

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Food security and public health are becoming major concerns for the global leaders due to climate change. The uneven distribution of rainfall and temperature has increased the global food demand with quality food. The current study was carried out for analysis of genetic diversity among 64 bread wheat genotypes for heat tolerance based on 21 morpho-physiological traits. The sixty four genotypes were grouped into five different clusters. Maximum number of genotypes was in cluster V (17) with lowest intra cluster distance (3.866) followed by cluster II (15), I (14), III and IV (each having 9 gen

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Tüzüntürk, Selim. "Clustering Türkiye's Provinces According to Education Level Indicators with Two-Stage Cluster Analysis." Akademik Araştırmalar ve Çalışmalar Dergisi (AKAD) 16, no. 31 (2024): 331–44. http://dx.doi.org/10.20990/kilisiibfakademik.1507942.

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Abstract Purpose: This study aims to cluster similar provinces of Turkey according to (i) below-high school and (ii) high school and above-high school education level indicators using cluster analysis methods. Design/Methodology: The annual most recent data for 81 provinces were taken from the education statistics for the year 2022 published on the official website of the Turkish Statistical Institute. A two-stage cluster analysis method was used to identify similar provinces. Findings: According to indicators of education level below the high school level, the first cluster consists of 17 pro

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Kumar, Vikas, Olga Smirnova, and Lyudmila Chesnyukova. "Technological development of smart industrial regions in Russia: A cluster analysis." E3S Web of Conferences 435 (2023): 03001. http://dx.doi.org/10.1051/e3sconf/202343503001.

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The article is intended to assess the level of technological development of Russian industrial regions using the method of statistical cluster analysis and discusses some special features associated with the formation of smart (promising) regional clusters. The work is based on the statistical data on production capacity, investments in scientific and technological progress, the level of production automation and other indicators characterizing the technological development of industry sectors. We evaluate these indicators and identify the regions with the highest level of technological develo

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GIACOMIN, VALERIA. "The Emergence of an Export Cluster: Traders and Palm Oil in Early Twentieth-Century Southeast Asia." Enterprise & Society 19, no. 2 (2017): 272–308. http://dx.doi.org/10.1017/eso.2017.10.

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Malaysia and Indonesia account for 90 percent of global exports of palm oil, forming one of the largest agricultural clusters in the world. This article uses archival sources to trace how this cluster emerged from the rubber business in the era of British and Dutch colonialism. Specifically, the rise of palm oil in this region was due to three interrelated factors: (1) the institutional environment of the existing rubber cluster; (2) an established community of foreign traders; and (3) a trading hub in Singapore that offered a multitude of advanced services. This analysis stresses the historic

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Boshev, Dane, Mirjana Jankulovska, Sonja Ivanovska, and Ljupcho Jankuloski. "Assesment of winter wheat advanced lines by use of multivariate statistical analyses." Genetika 48, no. 3 (2016): 991–1001. http://dx.doi.org/10.2298/gensr1603991b.

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This study was conducted to evaluate 49 advanced lines of winter wheat (Triticum aestivum L.) for their morphoagronomic traits and to determine best criteria for selection of lines to be included in future breeding program. The material was assessed in two years experiment at two locations, using RCBD design with three replications. Ten quantitative traits: plant height, number of fertile tillers, spike length, number of spikelets per spike, number of grains per spike, weight of grain per spike and per plant, fertility, biological yield and harvest index were evaluated by PCA and two-way clust

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Hermansyah, Hermansyah, Agung Riyadi, and Rina Delfina. "Cluster Analysis of the Productivity of Nurses’ Work." Jurnal Keperawatan Indonesia 25, no. 3 (2022): 136–44. http://dx.doi.org/10.7454/jki.v25i3.1411.

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Productivity is a measure of performance, including effectiveness and efficiency. The importance of work productivity for nurses includes its evaluation role in contributing to continuous improvement. The purpose of this study is to determine the classification of nurses in clusters based on work productivity in the inpatient room. It is an analytic study with a cross-sectional design. The study sample were 130 nurses in the inpatient room at the Bengkulu Provincial Hospital, selected using the proportional random sampling technique. A questionnaire was employed for the data collection. Data a

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Perren, Gabriel I., Ruben A. Vázquez, Andrés E. Piatti, and André Moitinho. "OCAAT: automated analysis of star cluster colour-magnitude diagrams for gauging the local distance scale." Proceedings of the International Astronomical Union 10, S306 (2014): 298–300. http://dx.doi.org/10.1017/s1743921314011077.

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AbstractStar clusters are among the fundamental astrophysical objects used in setting the local distance scale. Despite its crucial importance, the accurate determination of the distances to the Magellanic Clouds (SMC/LMC) remains a fuzzy step in the cosmological distance ladder. The exquisite astrometry of the recently launched ESA Gaia mission is expected to deliver extremely accurate statistical parallaxes, and thus distances, to the SMC/LMC. However, an independent SMC/LMC distance determination via main sequence fitting of star clusters provides an important validation check point for the

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