A cost Malmquist productivity index capturing group performance

This paper develops an index for comparing the productivity of groups of operating units in cost terms when input prices are available. In that sense it represents an extension of a similar index available in the literature for comparing groups of units in terms of technical productivity in the absence of input prices. The index is decomposed to reveal the origins of differences in performance of the groups of units both in terms of technical and cost productivity. The index and its decomposition are of value in contexts where the need arises to compare units which perform the same function but they can be grouped by virtue of the fact that they operate in different contexts as might for example arise in comparisons of water or gas transmission companies operating in different countries.

Group or individual tinnitus therapy:what matters to participants?

Objective: To explore the 'active ingredient' of tinnitus therapy groups. Study design: The design was an inductive qualitative study informed by grounded theory. Eight participants, four from a tinnitus group and four from individual therapy with similar content, were invited to discuss their experiences of tinnitus therapy. The interviews were transcribed and analysed using a constant comparative approach. Results: The findings revealed that group experiences facilitate information exchange and social comparison, which facilitates coping. Conclusions: The human dynamics of groups may have an additional therapeutic benefit. © 2011 Informa Healthcare.

Searching for resilience in sustainable development:learning journeys in conservation

Resilience is a term that is gaining currency in conservation and sustainable development, though its meaning and value in this context is yet to be defined. Searching for Resilience in Sustainable Development examines ways in which resilience may be created within the web of ecological, socio-economic and cultural systems that make up the world in. The authors embark upon a learning journey exploring both robust and fragile systems and asking questions of groups and individuals actively involved in building or maintaining resilience.

Organizational culture, organizational climate, and collaborative capacity for planning

The objective of this study was to investigate the relationship of organizational culture and organizational climate on participant perceptions of collaborative capacity for planning, within the context of the Florida School Readiness Coalitions (FSRCs). Three hypotheses were proposed for study: First, that organizational culture would be correlated to organizational climate; second, that organizational culture would be correlated to collaborative capacity for planning; and the third that organizational climate would be correlated to collaborative capacity for planning. ^ A cross-sectional survey research design was used to obtain data from participants in 25 Florida School Readiness Coalitions. Pearson product-moment correlations were used to examine the association between the dependent variable, collaborative capacity for planning, and the independent variables, organizational culture and climate. Bivariate analyses revealed a significant level of association for five culture indicators to collaborative capacity for planning: motivation, interpersonal, service, supportive and individualistic indicators, and four climate indicators: cooperation, job satisfaction, organizational commitment, and role clarity. Findings suggest (a) a constructive culture and positive climate were present within the FSRCs during the period of study and (b) participants perceived that the collaborative capacity for planning existed. Hierarchical multiple regression, controlling for effects of participant demographics, were used to examine the degree to which organizational culture and climate predict collaborative capacity. The culture indicators, supportive and individualistic, and the climate indicator job satisfaction accounted for 46% of the variance in collaborative capacity for planning. No other indicators of the independent variables demonstrated significance. The findings suggests that (a) culture and climate should be studied together, (b) culture and climate are two constructs that may provide knowledge about the way community groups work together, and (c) the collaborative capacity of groups planning services such as the FSRCs may benefit through consideration of how culture and climate affect service planners' relationships, communication, and ability to achieve a mission or goal. Culture and climate may offer social workers new information about internal factors affecting the collaborative process. Further investigation of these constructs with other types of groups is warranted. ^

Three essays on labor liberalization and its effects on world economy

This dissertation consists of three theoretical essays on immigration, international trade and political economy. The first two essays analyze the political economy of immigration in developed countries. The third essay explores new ground on the effects of labor liberalization in developing countries. Trade economists have witnessed remarkable methodological developments in mathematical and game theoretical models during the last seventy years. This dissertation benefits from these advances to analyze economic issues related to immigration. The first essay applies a long run general equilibrium trade model similar to Krugman (1980), and blends it with the median voter ala-Mayer (1984) framework. The second essay uses a short run general equilibrium specific factor trade model similar to Jones (1975) and incorporates it with the median voter model similar to Benhabib (1997). The third essay employs a five stage game theoretical approach similar to Vogel (2007) and solves it by the method of backward induction. The first essay shows that labor liberalization is more likely to come about in societies that have more taste for varieties, and that workers and capital owners could share the same positive stance toward labor liberalization. In a dynamic model, it demonstrates that the median voter is willing to accept fewer immigrants in the first period in order to preserve her domestic political influence in the second period threatened by the naturalization of these immigrants. The second essay shows that the liberalization of labor depends on the host country's stock and distribution of capital, and the number of groups of skilled workers within each country. I demonstrate that the more types of goods both countries produce, the more liberal the host country is toward immigration. The third essay proposes a theory of free movement of goods and labor between two economies with imperfect labor contracts. The heart of my analysis lies in the determinants of talent development where individuals' decisions to emigrate are related to the fixed costs of emigration. Finally, free trade and labor affect income via an indirect effect on individuals' incentives to invest in the skill levels and a direct effect on the prices of goods.

A influência da perda de peso no perfil inflamatório de mulheres com síndrome dos ovários policísticos

The polycystic ovary syndrome (PCOS) is considered the most common endocrine disorder in reproductive age women, with a prevalence ranging from 15 to 20%. In addition to hormonal and reproductive changes, it is common in PCOS the presence of risk factors for developing cardiovascular disease (CVD) and diabetes mellitus, insulin resistance (IR), visceral obesity, chronic low-grade inflammation and dyslipidemia. Due to the high frequency of obesity associated with PCOS, weight loss is considered as the first-line treatment for the syndrome by improving metabolic and normalizes serum androgens, restoring reproductive function of these patients. Objectives: To evaluate the inflammatory markers and IR in women with PCOS and healthy ovulatory with different nutritional status and how these parameters are displayed after weight loss through caloric restriction in with Down syndrome. Methods: Tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6) and C-reactive protein (CRP) were assessed in serum samples from 40 women of childbearing age. The volunteers were divided into four groups: Group I (not eutrophic with PCOS, n = 12); Group II (not eutrophic without PCOS, n = 10), Group III (eutrophic with PCOS, n = 08) and Group IV (eutrophic without PCOS, n = 10). The categorization of groups was performed by body mass index (BMI), according to the World Health Organization (WHO) does not eutrophic, overweight and obesity (BMI> 25 kg / m²) and normal weight (BMI <24.9 kg / m²). IR was determined by HOMA-IR index. In the second phase of the study a controlled dietary intervention was performed and inflammatory parameters were evaluated in 21 overweight and obese women with PCOS, before and after weight loss. All patients received a low-calorie diet with reduction of 500 kcal / day of regular consumption with standard concentrations of macronutrients. Results: Phase 1: PCOS patients showed increased levels of CRP (p <0.01) and HOMAIR (p <0.01). When divided by BMI, both not eutrophic group with PCOS (I) as eutrophic with PCOS (III) showed increased levels of CRP (I = 2.35 ± 0,55mg / L and 2.63 ± III = 0,65mg / L; p <0.01) and HOMA-IR (I = 2.16 ± 2.54 and III = 1.07 ± 0.55; p <0.01). There were no differences in TNF-α and IL-6 between groups. Step 2: After the weight loss of 5% of the initial weight was reduced in all of the components of serum assessed inflammatory profile, PCR (154.75 ± 19:33) vs (78.06 ± 8.9) TNF α (10.89 ± 5.09) vs (6:39 ± 1:41) and IL6 (154.75 ± 19:33) vs (78.06 ± 08.09) (p <0:00) in association with improvement some hormonal parameters evaluated. Conclusion: PCOS contributed to the development of chronic inflammation and changes in glucose metabolism by increasing CRP, insulin and HOMA-IR, independent of nutritional status. The weight loss, caloric restriction has improved the inflammatory condition and hormonal status of the evaluated patients.

Ateliê biográfico de formação profissional: prática socioeducativa em Escola Judicial

In recent decades, debates have intensified about (auto) biographical narratives as devices of socio-educational practices, aligned to the educational setting of the XXI century which have stimulated a new educational perspective woven with epistemological and methodological training throughout life. Towards that scenario, the continued training in Judicial School has occupied important space for constitutional effectiveness and, on the other hand, has grown the demands of expanding knowledge and enhancing training practices, in turn, judicial practices. The aim is to analyze the reflective Group through "Professional Training biographical Workshop" with Bailiffs such as socio-educational practices in socio Judicial School, in the city of Natal /RN. It has highlighted the questions that guided this study: 1. What paths of experiences and knowledge shared by the Law Officials, Federal Appraisers in "Professional Training biographical Workshop" as reflective Group? 2. How is organized the reflective Group as practice in socio-professional training setting? 3. What contributions narratives of themselves bring to the bailiff in reflective Group on Judicial School? The theoretical assumptions are supported in the lifelong training in methodological and epistemological dimension of (auto) biographical knowledge (JOSSO, 2008, 2010, 2012; PINEAU, 2005, 2006; DOMINICÉ, 2010; DELORY-MOMBERGER, 2006, 2008; FREIRE, 1987, 1996, 2001; PASSEGGI, 2008; 2010; 2011; 2012). In 2009, 09 (nine) civil servants in post of Federal Appraiser Justice Official, law graduates participated in this research through eight (08) "Biographical Workshops of Professional Training", consisting of biographical practices and scenarios, enabling oral and written narratives about a memory that has meaning, relationship and tessituras between files, facts and feelings that reveal the perception of self and other, as well as mobilize and weave the training process. The experiences of speaking, writing and reading were constituted of spaces that facilitating the reconstruction of the trajectory of training and career awareness-making, helping to re-signify labor relations and lead to their own professional design. From this study, the reflective properties of groups have emerged, consisting of Reflexivity, Experience, Historicity, Reversibility, dialog and formability processes, with paths to social and educational practices in which professionals identify the meaning and significance of self and of the profession that are exercising. The expectation is to continue with the spirit of research to emerge from the participants responses to training practices in Judicial School, aligned with the new knowledge of understanding the human being, not only an object of his work, but also a social subject, co-participant in the process of re-signifying life and work in a permanent way.

Efeitos dos exercícios aeróbio contínuo e intervalado na variabilidade da frequência cardíaca em adultos jovens saudáveis. Ensaio clínico aleatório

The high-intensity interval exercise has been described as an option for increasing physical activity and its use also being suggested in the therapeutic management of many conditions such as diabetes mellitus and heart failure. However, the knowledge of its physiological effects and parameters that can assure greater safety for interval exercise prescription; especially its effect on short- and medium-term (24 hours after exercise) exercise recovery, need to be clarified. This study objective was to evaluate the effect of continuous and interval aerobic exercise on the cardiac autonomic control immediate and medium term (24 hours), by assessing heart rate variability (HRV). The present study is a randomized crossover clinical trial in which healthy young individuals with low level of physical activity had the VFC 24 hours measured by a heart rate sensor and portable accelerometer (3D eMotion HRV, Kuopio, Finland) before and after continuous aerobic exercise (60-70% HR max, 21 min.) and interval exercise (cycle 1 min. 80-90% HR max, 2 min. at 50-60% HR max, duration 21 min.). HRV was measured in the time and frequency domain and the sympathovagal balance determined by the ratio LF / HF. Nonlinear evaluation was calculated by Shannon entropy. The data demonstrated delayed heart rate recovery immediate after exercise and lower HR after 24 hours compared to pre intervention values, especially in the interval exercise group. There was a tendency to higher predominance and representatives index values of sympathetic stimulation during the day in interval exercise group; however, without statistical significance. The study results help to clarify the effects of interval exercise on the 24 hours following interval exercise, setting parameters for prescription and for further evaluation of groups with metabolic and cardiovascular diseases.

Classificador máquina de suporte vetorial com análise de Fourier aplicada em dados de EEG e EMG

The classifier support vector machine is used in several problems in various areas of knowledge. Basically the method used in this classier is to end the hyperplane that maximizes the distance between the groups, to increase the generalization of the classifier. In this work, we treated some problems of binary classification of data obtained by electroencephalography (EEG) and electromyography (EMG) using Support Vector Machine with some complementary techniques, such as: Principal Component Analysis to identify the active regions of the brain, the periodogram method which is obtained by Fourier analysis to help discriminate between groups and Simple Moving Average to eliminate some of the existing noise in the data. It was developed two functions in the software R, for the realization of training tasks and classification. Also, it was proposed two weights systems and a summarized measure to help on deciding in classification of groups. The application of these techniques, weights and the summarized measure in the classier, showed quite satisfactory results, where the best results were an average rate of 95.31% to visual stimuli data, 100% of correct classification for epilepsy data and rates of 91.22% and 96.89% to object motion data for two subjects.

Predicting Transcript Production Rates in Yeast With Sparse Linear Models

To provide biological insights into transcriptional regulation, a couple of groups have recently presented models relating the promoter DNA-bound transcription factors (TFs) to downstream gene’s mean transcript level or transcript production rates over time. However, transcript production is dynamic in response to changes of TF concentrations over time. Also, TFs are not the only factors binding to promoters; other DNA binding factors (DBFs) bind as well, especially nucleosomes, resulting in competition between DBFs for binding at same genomic location. Additionally, not only TFs, but also some other elements regulate transcription. Within core promoter, various regulatory elements influence RNAPII recruitment, PIC formation, RNAPII searching for TSS, and RNAPII initiating transcription. Moreover, it is proposed that downstream from TSS, nucleosomes resist RNAPII elongation.

Here, we provide a machine learning framework to predict transcript production rates from DNA sequences. We applied this framework in the S. cerevisiae yeast for two scenarios: a) to predict the dynamic transcript production rate during the cell cycle for native promoters; b) to predict the mean transcript production rate over time for synthetic promoters. As far as we know, our framework is the first successful attempt to have a model that can predict dynamic transcript production rates from DNA sequences only: with cell cycle data set, we got Pearson correlation coefficient Cp = 0.751 and coefficient of determination r2 = 0.564 on test set for predicting dynamic transcript production rate over time. Also, for DREAM6 Gene Promoter Expression Prediction challenge, our fitted model outperformed all participant teams, best of all teams, and a model combining best team’s k-mer based sequence features and another paper’s biologically mechanistic features, in terms of all scoring metrics.

Moreover, our framework shows its capability of identifying generalizable fea- tures by interpreting the highly predictive models, and thereby provide support for associated hypothesized mechanisms about transcriptional regulation. With the learned sparse linear models, we got results supporting the following biological insights: a) TFs govern the probability of RNAPII recruitment and initiation possibly through interactions with PIC components and transcription cofactors; b) the core promoter amplifies the transcript production probably by influencing PIC formation, RNAPII recruitment, DNA melting, RNAPII searching for and selecting TSS, releasing RNAPII from general transcription factors, and thereby initiation; c) there is strong transcriptional synergy between TFs and core promoter elements; d) the regulatory elements within core promoter region are more than TATA box and nucleosome free region, suggesting the existence of still unidentified TAF-dependent and cofactor-dependent core promoter elements in yeast S. cerevisiae; e) nucleosome occupancy is helpful for representing +1 and -1 nucleosomes’ regulatory roles on transcription.

Cogestion des ressources naturelles : une approche structurale pour quantifier la contribution des réseaux d'acteurs à la résilience des systèmes socio-écologiques

Alors que les activités anthropiques font basculer de nombreux écosystèmes vers des régimes fonctionnels différents, la résilience des systèmes socio-écologiques devient un problème pressant. Des acteurs locaux, impliqués dans une grande diversité de groupes — allant d’initiatives locales et indépendantes à de grandes institutions formelles — peuvent agir sur ces questions en collaborant au développement, à la promotion ou à l’implantation de pratiques plus en accord avec ce que l’environnement peut fournir. De ces collaborations répétées émergent des réseaux complexes, et il a été montré que la topologie de ces réseaux peut améliorer la résilience des systèmes socio-écologiques (SSÉ) auxquels ils participent. La topologie des réseaux d’acteurs favorisant la résilience de leur SSÉ est caractérisée par une combinaison de plusieurs facteurs : la structure doit être modulaire afin d’aider les différents groupes à développer et proposer des solutions à la fois plus innovantes (en réduisant l’homogénéisation du réseau), et plus proches de leurs intérêts propres ; elle doit être bien connectée et facilement synchronisable afin de faciliter les consensus, d’augmenter le capital social, ainsi que la capacité d’apprentissage ; enfin, elle doit être robuste, afin d’éviter que les deux premières caractéristiques ne souffrent du retrait volontaire ou de la mise à l’écart de certains acteurs. Ces caractéristiques, qui sont relativement intuitives à la fois conceptuellement et dans leur application mathématique, sont souvent employées séparément pour analyser les qualités structurales de réseaux d’acteurs empiriques. Cependant, certaines sont, par nature, incompatibles entre elles. Par exemple, le degré de modularité d’un réseau ne peut pas augmenter au même rythme que sa connectivité, et cette dernière ne peut pas être améliorée tout en améliorant sa robustesse. Cet obstacle rend difficile la création d’une mesure globale, car le niveau auquel le réseau des acteurs contribue à améliorer la résilience du SSÉ ne peut pas être la simple addition des caractéristiques citées, mais plutôt le résultat d’un compromis subtil entre celles-ci. Le travail présenté ici a pour objectifs (1), d’explorer les compromis entre ces caractéristiques ; (2) de proposer une mesure du degré auquel un réseau empirique d’acteurs contribue à la résilience de son SSÉ ; et (3) d’analyser un réseau empirique à la lumière, entre autres, de ces qualités structurales. Cette thèse s’articule autour d’une introduction et de quatre chapitres numérotés de 2 à 5. Le chapitre 2 est une revue de la littérature sur la résilience des SSÉ. Il identifie une série de caractéristiques structurales (ainsi que les mesures de réseaux qui leur correspondent) liées à l’amélioration de la résilience dans les SSÉ. Le chapitre 3 est une étude de cas sur la péninsule d’Eyre, une région rurale d’Australie-Méridionale où l’occupation du sol, ainsi que les changements climatiques, contribuent à l’érosion de la biodiversité. Pour cette étude de cas, des travaux de terrain ont été effectués en 2010 et 2011 durant lesquels une série d’entrevues a permis de créer une liste des acteurs de la cogestion de la biodiversité sur la péninsule. Les données collectées ont été utilisées pour le développement d’un questionnaire en ligne permettant de documenter les interactions entre ces acteurs. Ces deux étapes ont permis la reconstitution d’un réseau pondéré et dirigé de 129 acteurs individuels et 1180 relations. Le chapitre 4 décrit une méthodologie pour mesurer le degré auquel un réseau d’acteurs participe à la résilience du SSÉ dans lequel il est inclus. La méthode s’articule en deux étapes : premièrement, un algorithme d’optimisation (recuit simulé) est utilisé pour fabriquer un archétype semi-aléatoire correspondant à un compromis entre des niveaux élevés de modularité, de connectivité et de robustesse. Deuxièmement, un réseau empirique (comme celui de la péninsule d’Eyre) est comparé au réseau archétypique par le biais d’une mesure de distance structurelle. Plus la distance est courte, et plus le réseau empirique est proche de sa configuration optimale. La cinquième et dernier chapitre est une amélioration de l’algorithme de recuit simulé utilisé dans le chapitre 4. Comme il est d’usage pour ce genre d’algorithmes, le recuit simulé utilisé projetait les dimensions du problème multiobjectif dans une seule dimension (sous la forme d’une moyenne pondérée). Si cette technique donne de très bons résultats ponctuellement, elle n’autorise la production que d’une seule solution parmi la multitude de compromis possibles entre les différents objectifs. Afin de mieux explorer ces compromis, nous proposons un algorithme de recuit simulé multiobjectifs qui, plutôt que d’optimiser une seule solution, optimise une surface multidimensionnelle de solutions. Cette étude, qui se concentre sur la partie sociale des systèmes socio-écologiques, améliore notre compréhension des structures actorielles qui contribuent à la résilience des SSÉ. Elle montre que si certaines caractéristiques profitables à la résilience sont incompatibles (modularité et connectivité, ou — dans une moindre mesure — connectivité et robustesse), d’autres sont plus facilement conciliables (connectivité et synchronisabilité, ou — dans une moindre mesure — modularité et robustesse). Elle fournit également une méthode intuitive pour mesurer quantitativement des réseaux d’acteurs empiriques, et ouvre ainsi la voie vers, par exemple, des comparaisons d’études de cas, ou des suivis — dans le temps — de réseaux d’acteurs. De plus, cette thèse inclut une étude de cas qui fait la lumière sur l’importance de certains groupes institutionnels pour la coordination des collaborations et des échanges de connaissances entre des acteurs aux intérêts potentiellement divergents.

Transformative Learning Theory and Its Relevance to Managing Group Dynamics in a Competitive Work Environment

In any environment, group dynamics would exist. How we deal with it in a competitive work environment defines who we are using transformative learning. This paper provides useful information from a number of theorists who share perspectives on the complex nature of groups.

A Group-Enhanced Sprint Interval Training Program for Amateur Athletes

Sprint interval training (SIT) can elicit improvements in aerobic and anaerobic capacity. While variations in SIT protocols have been investigated, the influence of social processes cannot be overlooked. As research supports the use of groups to influence individual cognitions and behaviours, the current project assessed the effectiveness of a group-based intervention with participants conducting SIT. Specifically, 53 amateur athletes (age, 21.9 ± 2.9 years; 53% females) took part in a 4-week training program (3 sessions per week, 30-s “all-out” efforts with 4 min active recovery, repeated 4–6 times per session), and were assigned to “true group”, aggregate, or individual conditions. Results indicated no significant differences between groups for the physiological measures. With regards to training improvements from baseline for all participants— regardless of condition — significant main effects for time were identified for maximal oxygen uptake (2.5–2.8 mL·kg−1·min−1, p < 0.001, η2 = 0.03), time-trial performance (14–32 s, p < 0.001, η2 = 0.37), and anaerobic power (1.1–1.7 k·h−1, p < 0.001, η2 = 0.66). With regards to the psychological measures, significant main effects between groups were found for motivation (p = 0.033, η2 = 0.13), task self-efficacy (p = 0.018, η2 = 0.15), and scheduling self-efficacy (p = 0.003, η2 = 0.22). The true group experienced greater improvements in motivation than the individual condition, but the aggregate and individual conditions demonstrated greater increases in task and scheduling self-efficacy. Though the SIT paradigm employed induced training improvements similar to previous work, the group intervention was not able to further these improvements

Clustering in non-parametric multivariate analyses.

Non-parametric multivariate analyses of complex ecological datasets are widely used. Following appropriate pre-treatment of the data inter-sample resemblances are calculated using appropriate measures. Ordination and clustering derived from these resemblances are used to visualise relationships among samples (or variables). Hierarchical agglomerative clustering with group-average (UPGMA) linkage is often the clustering method chosen. Using an example dataset of zooplankton densities from the Bristol Channel and Severn Estuary, UK, a range of existing and new clustering methods are applied and the results compared. Although the examples focus on analysis of samples, the methods may also be applied to species analysis. Dendrograms derived by hierarchical clustering are compared using cophenetic correlations, which are also used to determine optimum  in flexible beta clustering. A plot of cophenetic correlation against original dissimilarities reveals that a tree may be a poor representation of the full multivariate information. UNCTREE is an unconstrained binary divisive clustering algorithm in which values of the ANOSIM R statistic are used to determine (binary) splits in the data, to form a dendrogram. A form of flat clustering, k-R clustering, uses a combination of ANOSIM R and Similarity Profiles (SIMPROF) analyses to determine the optimum value of k, the number of groups into which samples should be clustered, and the sample membership of the groups. Robust outcomes from the application of such a range of differing techniques to the same resemblance matrix, as here, result in greater confidence in the validity of a clustering approach.

Clustering in non-parametric multivariate analyses.

Non-parametric multivariate analyses of complex ecological datasets are widely used. Following appropriate pre-treatment of the data inter-sample resemblances are calculated using appropriate measures. Ordination and clustering derived from these resemblances are used to visualise relationships among samples (or variables). Hierarchical agglomerative clustering with group-average (UPGMA) linkage is often the clustering method chosen. Using an example dataset of zooplankton densities from the Bristol Channel and Severn Estuary, UK, a range of existing and new clustering methods are applied and the results compared. Although the examples focus on analysis of samples, the methods may also be applied to species analysis. Dendrograms derived by hierarchical clustering are compared using cophenetic correlations, which are also used to determine optimum  in flexible beta clustering. A plot of cophenetic correlation against original dissimilarities reveals that a tree may be a poor representation of the full multivariate information. UNCTREE is an unconstrained binary divisive clustering algorithm in which values of the ANOSIM R statistic are used to determine (binary) splits in the data, to form a dendrogram. A form of flat clustering, k-R clustering, uses a combination of ANOSIM R and Similarity Profiles (SIMPROF) analyses to determine the optimum value of k, the number of groups into which samples should be clustered, and the sample membership of the groups. Robust outcomes from the application of such a range of differing techniques to the same resemblance matrix, as here, result in greater confidence in the validity of a clustering approach.