Cluster Analysis Applied to a Study of Race Mixture in Human Populations

1977 ◽  
pp. 175-197 ◽  
Author(s):  
C. Radhakrishna Rao
Keyword(s):  
Cluster Analysis ◽  
Human Populations

scholarly journals Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0244413
Author(s):  
Beneditta Suwono ◽  
Tim Eckmanns ◽  
Heike Kaspar ◽  
Roswitha Merle ◽  
Benedikt Zacher ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Cluster Analysis ◽  
One Health ◽  
Average Distance ◽  
Companion Animals ◽  
Clinical Isolates ◽  
Human Populations ◽  
Animal Populations ◽  
Routine Surveillance ◽  
Animal Isolates

Recent findings on Antibiotic Resistance (AR) have brought renewed attention to the comparison of data on AR from human and animal sectors. This is however a major challenge since the data is not harmonized. This study performs a comparative analysis of data on resistance combinations in Escherichia coli (E. coli) from different routine surveillance and monitoring systems for human and different animal populations in Germany. Data on E. coli isolates were collected between 2014 and 2017 from human clinical isolates, non-clinical animal isolates from food-producing animals and food, and clinical animal isolates from food-producing and companion animals from national routine surveillance and monitoring for AR in Germany. Sixteen possible resistance combinations to four antibiotics—ampicillin, cefotaxime, ciprofloxacin and gentamicin–for these populations were used for hierarchical clustering (Euclidian and average distance). All analyses were performed with the software R 3.5.1 (Rstudio 1.1.442). Data of 333,496 E. coli isolates and forty-one different human and animal populations were included in the cluster analysis. Three main clusters were detected. Within these three clusters, all human populations (intensive care unit (ICU), general ward and outpatient care) showed similar relative frequencies of the resistance combinations and clustered together. They demonstrated similarities with clinical isolates from different animal populations and most isolates from pigs from both non-clinical and clinical isolates. Isolates from healthy poultry demonstrated similarities in relative frequencies of resistance combinations and clustered together. However, they clustered separately from the human isolates. All isolates from different animal populations with low relative frequencies of resistance combinations clustered together. They also clustered separately from the human populations. Cluster analysis has been able to demonstrate the linkage among human isolates and isolates from various animal populations based on the resistance combinations. Further analyses based on these findings might support a better one-health approach for AR in Germany.

scholarly journals Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017

2020 ◽  
Author(s):  
Beneditta Suwono ◽  
Tim Eckmanns ◽  
Heike Kaspar ◽  
Roswitha Merle ◽  
Benedikt Zacher ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Cluster Analysis ◽  
Average Distance ◽  
Companion Animals ◽  
Clinical Isolates ◽  
Human Populations ◽  
E Coli ◽  
Animal Populations ◽  
Routine Surveillance ◽  
Animal Isolates

Abstract Recent findings on Antibiotic Resistance (AR) have brought renewed attention to the comparison of data on AR from human and animal sectors. This is however, a major challenge since the data is not harmonized. This study performs a comparative analysis of data on resistance combinations in Escherichia coli (E. coli) from different routine surveillance and monitoring systems for human and different animal populations in Germany. Data on E. coli isolates were collected between 2014 and 2017 from human clinical isolates, non-clinical animal isolates from food-producing animals and food, and clinical animal isolates from food-producing and companion animals from national routine surveillance and monitoring for AR in Germany. Sixteen possible resistance combinations to four antibiotics - ampicillin, cefotaxime, ciprofloxacin and gentamicin – for these populations were used for hierarchical clustering (Euclidian and average distance). All analyses were performed with the software R 3.5.1 (Rstudio 1.1.442). Data of 333,496 E. coli isolates and forty-one different human and animal populations were included in the cluster analysis. Three main clusters were detected. Within these three clusters, all human populations (intensive care unit (ICU), general ward and outpatient care) showed similar relative frequencies of the resistance combinations and clustered together. They demonstrated similarities with clinical isolates from different animal populations and most isolates from pigs from both non-clinical and clinical isolates. Isolates from healthy poultry demonstrated similarities in relative frequencies of resistance combinations and clustered together. However, they clustered separately from the human isolates. All isolates from different animal populations with low relative frequencies of resistance combinations clustered together and likewise separately from the human populations. Cluster analysis has been able to demonstrate the linkage among human isolates and isolates from various animal populations based on the resistance combinations. Further analyses based on these findings might promote a better one-health approach for AR in Germany.

scholarly journals Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017

2020 ◽  
Author(s):  
Beneditta Suwono ◽  
Tim Eckmanns ◽  
Heike Kaspar ◽  
Roswitha Merle ◽  
Benedikt Zacher ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Cluster Analysis ◽  
Average Distance ◽  
Companion Animals ◽  
Clinical Isolates ◽  
Human Populations ◽  
E Coli ◽  
Animal Populations ◽  
Routine Surveillance ◽  
Resistance Patterns

Abstract Background Recent findings on Antibiotic Resistance (AR) have brought renewed attention to the comparison of data on AR from human and animal sectors. This is however, a major challenge since the data is not harmonized. This study performs a comparative analysis of phenotypical AR data from different routine surveillance and monitoring systems in Germany. Escherichia coli data were used as a model to describe the similarities based on the resistance patterns in human and different animal populations in Germany. Method: Data on E. coli isolates were collected from 2014 to 2017 from human clinical isolates, non-clinical isolates from food-producing animals and food, and clinical isolates from food-producing and companion animals from national routine surveillance and monitoring for AR in Germany. Four antibiotics - ampicillin, cefotaxime, ciprofloxacin and gentamicin - were chosen for the analysis. Resistant isolates were defined according to EUCAST clinical breakpoints for humans. Based on the 16 possible resistance combinations to these four antibiotics, cluster analysis was performed using hierarchical clustering with Euclidian and average distance. All analyses were performed with the software “R”. Result Data of 333,496 E. coli isolates were included in this study. Forty-one different human and animal populations were included in the cluster analysis. Three main clusters were detected. Within these three clusters, all human populations (intensive care unit (ICU), general ward and outpatient care) showed similar relative frequencies of the resistance combinations and clustered together. They demonstrated similarities with clinical isolates from different animal populations and most isolates from pigs from both non-clinical and clinical isolates. Isolates from healthy poultry demonstrated similarities in relative frequencies of resistance combinations and clustered together. However, they clustered separately from the human isolates. All isolates from different animal populations with low relative frequencies of resistance combinations clustered together and likewise separately from the human populations. Conclusion Cluster analysis facilitated the comparison of phenotypical AR data across human and animal sectors. It indicated linkage among human isolates and with isolates from various animal populations based on the resistance combinations in E. coli. Further analyses based on these findings might promote a better one-health approach for AR in Germany.

The sense of obligation is culturally modulated

2020 ◽  
Vol 43 ◽  
Author(s):  
Andrea Bender
Keyword(s):  
Cultural Studies ◽  
Cross Cultural ◽  
Human Populations ◽  
Cultural Group ◽  
Target Article ◽  
Sense Of Obligation ◽  
Cross Cultural Studies

Abstract Tomasello argues in the target article that, in generalizing the concrete obligations originating from interdependent collaboration to one's entire cultural group, humans become “ultra-cooperators.” But are all human populations cooperative in similar ways? Based on cross-cultural studies and my own fieldwork in Polynesia, I argue that cooperation varies along several dimensions, and that the underlying sense of obligation is culturally modulated.

Cluster analysis for large data sets: applications to individual aerosol particles from the mid-pacific

1992 ◽  
Vol 50 (2) ◽  
pp. 1488-1489
Author(s):  
Thomas W. Shattuck ◽  
James R. Anderson ◽  
Neil W. Tindale ◽  
Peter R. Buseck
Keyword(s):  
Cluster Analysis ◽  
Chemical Reactivity ◽  
Large Data ◽  
Large Data Sets ◽  
Particle Analysis ◽  
Data Sets ◽  
Halogen Chemistry ◽  
Complete Study ◽  
Components Analysis ◽  
Automated Scanning

Individual particle analysis involves the study of tens of thousands of particles using automated scanning electron microscopy and elemental analysis by energy-dispersive, x-ray emission spectroscopy (EDS). EDS produces large data sets that must be analyzed using multi-variate statistical techniques. A complete study uses cluster analysis, discriminant analysis, and factor or principal components analysis (PCA). The three techniques are used in the study of particles sampled during the FeLine cruise to the mid-Pacific ocean in the summer of 1990. The mid-Pacific aerosol provides information on long range particle transport, iron deposition, sea salt ageing, and halogen chemistry.Aerosol particle data sets suffer from a number of difficulties for pattern recognition using cluster analysis. There is a great disparity in the number of observations per cluster and the range of the variables in each cluster. The variables are not normally distributed, they are subject to considerable experimental error, and many values are zero, because of finite detection limits. Many of the clusters show considerable overlap, because of natural variability, agglomeration, and chemical reactivity.

Measuring “Language Access Profiles” in Deaf and Hard-of-Hearing Children With the DHH Language Exposure Assessment Tool

2020 ◽  
pp. 1-25
Author(s):  
Matthew L. Hall ◽  
Stephanie De Anda
Keyword(s):  
Cluster Analysis ◽  
Exposure Assessment ◽  
Hard Of Hearing ◽  
Assessment Tool ◽  
Communication Mode ◽  
Developmental Potential ◽  
Language Access ◽  
Retest Reliability ◽  
Language Exposure ◽  
Test Retest Reliability

Purpose The purposes of this study were (a) to introduce “language access profiles” as a viable alternative construct to “communication mode” for describing experience with language input during early childhood for deaf and hard-of-hearing (DHH) children; (b) to describe the development of a new tool for measuring DHH children's language access profiles during infancy and toddlerhood; and (c) to evaluate the novelty, reliability, and validity of this tool. Method We adapted an existing retrospective parent report measure of early language experience (the Language Exposure Assessment Tool) to make it suitable for use with DHH populations. We administered the adapted instrument (DHH Language Exposure Assessment Tool [D-LEAT]) to the caregivers of 105 DHH children aged 12 years and younger. To measure convergent validity, we also administered another novel instrument: the Language Access Profile Tool. To measure test–retest reliability, half of the participants were interviewed again after 1 month. We identified groups of children with similar language access profiles by using hierarchical cluster analysis. Results The D-LEAT revealed DHH children's diverse experiences with access to language during infancy and toddlerhood. Cluster analysis groupings were markedly different from those derived from more traditional grouping rules (e.g., communication modes). Test–retest reliability was good, especially for the same-interviewer condition. Content, convergent, and face validity were strong. Conclusions To optimize DHH children's developmental potential, stakeholders who work at the individual and population levels would benefit from replacing communication mode with language access profiles. The D-LEAT is the first tool that aims to measure this novel construct. Despite limitations that future work aims to address, the present results demonstrate that the D-LEAT represents progress over the status quo.

Social representations of human rights violations: Further evidence

2001 ◽  
Vol 60 (2) ◽  
pp. 89-98 ◽  
Author(s):  
Alain Clémence ◽  
Thierry Devos ◽  
Willem Doise
Keyword(s):  
Cluster Analysis ◽  
Human Rights ◽  
Costa Rica ◽  
Young People ◽  
Social Representations ◽  
Social Reality ◽  
Questionnaire Study ◽  
Human Rights Violations ◽  
High Tolerance ◽  
Individual Actions

Social representations of human rights violations were investigated in a questionnaire study conducted in five countries (Costa Rica, France, Italy, Romania, and Switzerland) (N = 1239 young people). We were able to show that respondents organize their understanding of human rights violations in similar ways across nations. At the same time, systematic variations characterized opinions about human rights violations, and the structure of these variations was similar across national contexts. Differences in definitions of human rights violations were identified by a cluster analysis. A broader definition was related to critical attitudes toward governmental and institutional abuses of power, whereas a more restricted definition was rooted in a fatalistic conception of social reality, approval of social regulations, and greater tolerance for institutional infringements of privacy. An atypical definition was anchored either in a strong rejection of social regulations or in a strong condemnation of immoral individual actions linked with a high tolerance for governmental interference. These findings support the idea that contrasting definitions of human rights coexist and that these definitions are underpinned by a set of beliefs regarding the relationships between individuals and institutions.

Self-Injurious Behavior vs. Nonsuicidal Self-Injury

Crisis ◽  
2012 ◽  
Vol 33 (2) ◽  
pp. 106-112 ◽  
Author(s):  
Christopher M. Bloom ◽  
Shareen Holly ◽  
Adam M. P. Miller
Keyword(s):  
Positive Reinforcement ◽  
Empirical Investigation ◽  
High Stress ◽  
Animal Research ◽  
Stress Conditions ◽  
Human Populations ◽  
Pharmacological Interventions ◽  
Self Injury ◽  
Cns Stimulant ◽  
Nonsuicidal Self Injury

Background: Historically, the field of self-injury has distinguished between the behaviors exhibited among individuals with a developmental disability (self-injurious behaviors; SIB) and those present within a normative population (nonsuicidal self-injury; NSSI),which typically result as a response to perceived stress. More recently, however, conclusions about NSSI have been drawn from lines of animal research aimed at examining the neurobiological mechanisms of SIB. Despite some functional similarity between SIB and NSSI, no empirical investigation has provided precedent for the application of SIB-targeted animal research as justification for pharmacological interventions in populations demonstrating NSSI. Aims: The present study examined this question directly, by simulating an animal model of SIB in rodents injected with pemoline and systematically manipulating stress conditions in order to monitor rates of self-injury. Methods: Sham controls and experimental animals injected with pemoline (200 mg/kg) were assigned to either a low stress (discriminated positive reinforcement) or high stress (discriminated avoidance) group and compared on the dependent measures of self-inflicted injury prevalence and severity. Results: The manipulation of stress conditions did not impact the rate of self-injury demonstrated by the rats. The results do not support a model of stress-induced SIB in rodents. Conclusions: Current findings provide evidence for caution in the development of pharmacotherapies of NSSI in human populations based on CNS stimulant models. Theoretical implications are discussed with respect to antecedent factors such as preinjury arousal level and environmental stress.

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