Further E. K. Means. Is this a title? It is not. It is the name of a writer of Negro stories, who has made himself so completely the writer of Negro stories that this third book, like the first and second, needs no title.

The left hind foot.-- The f̓raid cat.-- The consolation prize.-- The first high janitor.-- Family ties.-- The ten-share horse.-- A chariot of fire.

Sea surface and the sea floor regionalization of the Southern Ocean by multivariate cluster analysis, links to ArcGIS project files

This study subdivides the Weddell Sea, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis uses 28 environmental variables for the sea surface, 25 variables for the seabed and 9 variables for the analysis between surface and bottom variables. The data were taken during the years 1983-2013. Some data were interpolated. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared for the identification of the most reasonable method. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested. For the seabed 8 and 12 clusters were identified as reasonable numbers for clustering the Weddell Sea. For the sea surface the numbers 8 and 13 and for the top/bottom analysis 8 and 3 were identified, respectively. Additionally, the results of 20 clusters are presented for the three alternatives offering the first small scale environmental regionalization of the Weddell Sea. Especially the results of 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.

New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM)

LEÃO, Adriano de Castro; DÓRIA NETO, Adrião Duarte; SOUSA, Maria Bernardete Cordeiro de. New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM). Computers in Biology and Medicine, v. 39, p. 853-859, 2009

K-means Classification

Resources created at the University of Southampton for the module Remote Sensing for Earth Observation

New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM)

LEÃO, Adriano de Castro; DÓRIA NETO, Adrião Duarte; SOUSA, Maria Bernardete Cordeiro de. New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM). Computers in Biology and Medicine, v. 39, p. 853-859, 2009

Consumer acceptance of high pressure processed beef-based chilled ready meals: The mediating role of food-related lifestyle factors

The aim of this research was to investigate the effects of high pressure processing (HPP) on consumer acceptance for chilled ready meals manufactured using a low-value beef cut. Three hundred consumers evaluated chilled ready meals subjected to 4 pressure treatments and a non-treated control monadically on a 9-point scale for liking for beef tenderness and juiciness, overall flavour, overall liking, and purchase intent. Data were also collected on consumers' food consumption patterns, their attitudes towards food by means of the reduced food-related lifestyle (FRL) instrument, and socio-demographics. The results indicated that a pressure treatment of 200 MPa was acceptable to most consumers. K-means cluster analysis identified 4 consumer groups with similar preferences, and the optimal pressure treatments acceptable to specific consumer groups were identified for those firms that would wish to target attitudinally differentiated consumer segments

Environmental factors, spatial variation, and specific requirements of Chironomidae in Mediterranean reference streams

Chironomidae spatial distribution was investigated at 63 near-pristine sites in 22 catchments of the Iberian Mediterranean coast. We used partial redundancy analysis to study Chironomidae community responses to a number of environmental factors acting at several spatial scales. The percentage of variation explained by local factors (23.3%) was higher than that explained by geographical (8.5%) or regional factors(8%). Catchment area, longitude, pH, % siliceous rocks in the catchment, and altitude were the best predictors of Chironomidae assemblages. We used a k-means cluster analysis to classified sites into 3 major groups based on Chironomidae assemblages. These groups were explained mainly by longitudinal zonation and geographical position, and were defined as 1) siliceous headwater streams, 2) mid-altitude streams with small catchment areas, and 3) medium-sized calcareous streams. Distinct species assemblages with associated indicator taxa were established for each stream category using IndVal analysis. Species responses to previously identified key environmental variables were determined, and optima and tolerances were established by weighted average regression. Distinct ecological requirements were observed among genera and among species of the same genus. Some genera were restricted to headwater systems (e.g., Diamesa), whereas others (e.g., Eukiefferiella) had wider ecological preferences but with distinct distributions among congenerics. In the present period of climate change, optima and tolerances of species might be a useful tool to predict responses of different species to changes in significant environmental variables, such as temperature and hydrology.

Identifying first graders at risk of reading and writing difficulties : creating a group-based screening tool in kiswahili in Tanzania

Early identification of beginning readers at risk of developing reading and writing difficulties plays an important role in the prevention and provision of appropriate intervention. In Tanzania, as in other countries, there are children in schools who are at risk of developing reading and writing difficulties. Many of these children complete school without being identified and without proper and relevant support. The main language in Tanzania is Kiswahili, a transparent language. Contextually relevant, reliable and valid instruments of identification are needed in Tanzanian schools. This study aimed at the construction and validation of a group-based screening instrument in the Kiswahili language for identifying beginning readers at risk of reading and writing difficulties. In studying the function of the test there was special interest in analyzing the explanatory power of certain contextual factors related to the home and school. Halfway through grade one, 337 children from four purposively selected primary schools in Morogoro municipality were screened with a group test consisting of 7 subscales measuring phonological awareness, word and letter knowledge and spelling. A questionnaire about background factors and the home and school environments related to literacy was also used. The schools were chosen based on performance status (i.e. high, good, average and low performing schools) in order to include variation. For validation, 64 children were chosen from the original sample to take an individual test measuring nonsense word reading, word reading, actual text reading, one-minute reading and writing. School marks from grade one and a follow-up test half way through grade two were also used for validation. The correlations between the results from the group test and the three measures used for validation were very high (.83-.95). Content validity of the group test was established by using items drawn from authorized text books for reading in grade one. Construct validity was analyzed through item analysis and principal component analysis. The difficulty level of most items in both the group test and the follow-up test was good. The items also discriminated well. Principal component analysis revealed one powerful latent dimension (initial literacy factor), accounting for 93% of the variance. This implies that it could be possible to use any set of the subtests of the group test for screening and prediction. The K-Means cluster analysis revealed four clusters: at-risk children, strugglers, readers and good readers. The main concern in this study was with the groups of at-risk children (24%) and strugglers (22%), who need the most assistance. The predictive validity of the group test was analyzed by correlating the measures from the two school years and by cross tabulating grade one and grade two clusters. All the correlations were positive and very high, and 94% of the at-risk children in grade two were already identified in the group test in grade one. The explanatory power of some of the home and school factors was very strong. The number of books at home accounted for 38% of the variance in reading and writing ability measured by the group test. Parents´ reading ability and the support children received at home for schoolwork were also influential factors. Among the studied school factors school attendance had the strongest explanatory power, accounting for 21% of the variance in reading and writing ability. Having been in nursery school was also of importance. Based on the findings in the study a short version of the group test was created. It is suggested for use in the screening processes in grade one aiming at identifying children at risk of reading and writing difficulties in the Tanzanian context. Suggestions for further research as well as for actions for improving the literacy skills of Tanzanian children are presented.

Dendritic thickness: a morphometric parameter to classify mouse retinal ganglion cells

To study the dendritic morphology of retinal ganglion cells in wild-type mice we intracellularly injected these cells with Lucifer yellow in an in vitro preparation of the retina. Subsequently, quantified values of dendritic thickness, number of branching points and level of stratification of 73 Lucifer yellow-filled ganglion cells were analyzed by statistical methods, resulting in a classification into 9 groups. The variables dendritic thickness, number of branching points per cell and level of stratification were independent of each other. Number of branching points and level of stratification were independent of eccentricity, whereas dendritic thickness was positively dependent (r = 0.37) on it. The frequency distribution of dendritic thickness tended to be multimodal, indicating the presence of at least two cell populations composed of neurons with dendritic diameters either smaller or larger than 1.8 µm ("thin" or "thick" dendrites, respectively). Three cells (4.5%) were bistratified, having thick dendrites, and the others (95.5%) were monostratified. Using k-means cluster analysis, monostratified cells with either thin or thick dendrites were further subdivided according to level of stratification and number of branching points: cells with thin dendrites were divided into 2 groups with outer stratification (0-40%) and 2 groups with inner (50-100%) stratification, whereas cells with thick dendrites were divided into one group with outer and 3 groups with inner stratification. We postulate, that one group of cells with thin dendrites resembles cat ß-cells, whereas one group of cells with thick dendrites includes cells that resemble cat a-cells.

Psychographic characteristics of weekend wine tourists : a multiple case study of four wineries in the Niagara Region

The purpose of this study is to examine the psychographic (product attributes, motivation opinions, interest, lifestyle, values) characteristics of wine tourists along the Niagara wine r,~ute, located in Ontario, Canada, using a multiple case study method. Four wineries were selected, two wineries each on the East, and West sides of the wine route during the shoulder-season (January, February, 2004). Using a computer generated survey technique, tourists were approached to fill out a questionnaire on one of the available laptop computers, where a sample ofN=321 was obtained. The study findings revealed that there are three distinct wine tourist segments in the Niagara region. The segments were determined using an exploratory factor analysis (EFA) and a K-means cluster analysis: Wine Lovers, Wine Interested, and Wine Curious wine tourists. These three segments displayed significant differences in their, motivation for visiting a winery, lifestyles, values, and wine purchasing behaviour. This study also examined differences between winery locations, on the East and West sides of the Niagara wine route, with respect to the aforementioned variables. The results indicated that there were significant differences between the regions with respect to these variables. The findings suggest that these differences present opportunities for more effective marketing strategies based on the uniqueness of each region. The results of this study provide insight for academia into a method of psychographic market segmentation of wine tourists and consumer behaviour. This study also contributes to the literature on wine tourism, and the identification of psychographic characteristics of wine tourists, an area where little research has taken place.

A continuum of sudden stratospheric warmings

The k-means cluster technique is used to examine 43 yr of daily winter Northern Hemisphere (NH) polar stratospheric data from the 40-yr ECMWF Re-Analysis (ERA-40). The results show that the NH winter stratosphere exists in two natural well-separated states. In total, 10% of the analyzed days exhibit a warm disturbed state that is typical of sudden stratospheric warming events. The remaining 90% of the days are in a state typical of a colder undisturbed vortex. These states are determined objectively, with no preconceived notion of the groups. The two stratospheric states are described and compared with alternative indicators of the polar winter flow, such as the northern annular mode. It is shown that the zonally averaged zonal winds in the polar upper stratosphere at 7 hPa can best distinguish between the two states, using a threshold value of 4 m s−1, which is remarkably close to the standard WMO criterion for major warming events. The analysis also determines that there are no further divisions within the warm state, indicating that there is no well-designated threshold between major and minor warmings, nor between split and displaced vortex events. These different manifestations are simply members of a continuum of warming events.

Estimation of wind storm impacts over Western Germany under future climate conditions using a statistical-dynamical downscaling approach

A statistical–dynamical regionalization approach is developed to assess possible changes in wind storm impacts. The method is applied to North Rhine-Westphalia (Western Germany) using the FOOT3DK mesoscale model for dynamical downscaling and ECHAM5/OM1 global circulation model climate projections. The method first classifies typical weather developments within the reanalysis period using K-means cluster algorithm. Most historical wind storms are associated with four weather developments (primary storm-clusters). Mesoscale simulations are performed for representative elements for all clusters to derive regional wind climatology. Additionally, 28 historical storms affecting Western Germany are simulated. Empirical functions are estimated to relate wind gust fields and insured losses. Transient ECHAM5/OM1 simulations show an enhanced frequency of primary storm-clusters and storms for 2060–2100 compared to 1960–2000. Accordingly, wind gusts increase over Western Germany, reaching locally +5% for 98th wind gust percentiles (A2-scenario). Consequently, storm losses are expected to increase substantially (+8% for A1B-scenario, +19% for A2-scenario). Regional patterns show larger changes over north-eastern parts of North Rhine-Westphalia than for western parts. For storms with return periods above 20 yr, loss expectations for Germany may increase by a factor of 2. These results document the method's functionality to assess future changes in loss potentials in regional terms.

Análise de DFA e de agrupamento do perfil de densidade de poços de petróleo

In recent years, the DFA introduced by Peng, was established as an important tool capable of detecting long-range autocorrelation in time series with non-stationary. This technique has been successfully applied to various areas such as: Econophysics, Biophysics, Medicine, Physics and Climatology. In this study, we used the DFA technique to obtain the Hurst exponent (H) of the profile of electric density profile (RHOB) of 53 wells resulting from the Field School of Namorados. In this work we want to know if we can or not use H to spatially characterize the spatial data field. Two cases arise: In the first a set of H reflects the local geology, with wells that are geographically closer showing similar H, and then one can use H in geostatistical procedures. In the second case each well has its proper H and the information of the well are uncorrelated, the profiles show only random fluctuations in H that do not show any spatial structure. Cluster analysis is a method widely used in carrying out statistical analysis. In this work we use the non-hierarchy method of k-means. In order to verify whether a set of data generated by the k-means method shows spatial patterns, we create the parameter Ω (index of neighborhood). High Ω shows more aggregated data, low Ω indicates dispersed or data without spatial correlation. With help of this index and the method of Monte Carlo. Using Ω index we verify that random cluster data shows a distribution of Ω that is lower than actual cluster Ω. Thus we conclude that the data of H obtained in 53 wells are grouped and can be used to characterize space patterns. The analysis of curves level confirmed the results of the k-means

Dendritic thickness: a morphometric parameter to classify mouse retinal ganglion cells

To study the dendritic morphology of retinal ganglion cells in wild-type mice we intracellularly injected these cells with Lucifer yellow in an in vitro preparation of the retina. Subsequently, quantified values of dendritic thickness, number of branching points and level of stratification of 73 Lucifer yellow-filled ganglion cells were analyzed by statistical methods, resulting in a classification into 9 groups. The variables dendritic thickness, number of branching points per cell and level of stratification were independent of each other. Number of branching points and level of stratification were independent of eccentricity, whereas dendritic thickness was positively dependent (r = 0.37) on it. The frequency distribution of dendritic thickness tended to be multimodal, indicating the presence of at least two cell populations composed of neurons with dendritic diameters either smaller or larger than 1.8 µm ("thin" or "thick" dendrites, respectively). Three cells (4.5%) were bistratified, having thick dendrites, and the others (95.5%) were monostratified. Using k-means cluster analysis, monostratified cells with either thin or thick dendrites were further subdivided according to level of stratification and number of branching points: cells with thin dendrites were divided into 2 groups with outer stratification (0-40%) and 2 groups with inner (50-100%) stratification, whereas cells with thick dendrites were divided into one group with outer and 3 groups with inner stratification. We postulate, that one group of cells with thin dendrites resembles cat ß-cells, whereas one group of cells with thick dendrites includes cells that resemble cat a-cells.