Metal concentrations in soils around the copper smelter and surrounding industrial complex of Port Kembla, NSW, Australia

Anthropogenic emissions of metals from sources such as smelters are an international problem, but there is limited published information on emissions from Australian smelters. The objective of this study was to investigate the regional distribution of heavy metals in soils in the vicinity of the industrial complex of Port Kembla, NSW, Australia, which comprises a copper smelter, steelworks and associated industries. Soil samples (n=25) were collected at the depths of 0-5 and 5-20 cm, air dried and sieved to < 2 mm. Aqua regia extractable amounts of As, Cr, Cu, Ph and Zn were analysed by inductively coupled plasma mass spectrometry (lCP-MS) and inductively coupled plasma atomic emission spectrometry (ICP-AES). Outliers were identified from background levels by statistical methods. Mean background levels at a depth of 0-5 cm were estimated at 3.2 mg/kg As, 12 mg/kg Cr, 49 mg/kg Cu, 20 mg/kg Ph and 42 mg/kg Zn. Outliers for elevated As and Cu values were mainly present within 4 km from the Port Kembla industrial complex, but high Ph at two sites and high Zn concentrations were found at six sites up to 23 km from Port Kembla. Chromium concentrations were not anomalous close to the industrial complex. There was no significant difference of metal concentrations at depths of 0-5 and 5-20 cm, except for Ph and Zn. Copper and As concentrations in the soils are probably related to the concentrations in the parent rock. From this investigation, the extent of the contamination emanating from the Port Kembla industrial complex is limited to 1-13 km, but most likely <4 km, depending on the element; the contamination at the greater distance may not originate from the industrial complex. (C) 2003 Elsevier B.V. All rights reserved.

Instrumental leadership: An extension of the Full-Range Leadership Theory

From a theoretical perspective, an extension to the Full Range leadership Theory (FRLT) seems needed. In this paper, we explain why instrumental leadership--a class of leadership includes leader behaviors focusing on task and strategic aspects that are neither values nor exchange oriented--can fulfill this extension. Instrument leadership is composed of four factors: environmental monitoring, strategy formulation and implementation, path-goal facilitation and outcome monitoring; these aspects of leadership are currently not included in any of the FRLT's nine leadership scales (as measured by the MLQ--Multifactor Leadership Questionnaire). We present results from two empirical studies using very large samples from a wide array of countries (N > 3,000) to examine the factorial, discriminant and criterion-related validity of the instrumental leadership scales. We find support for a four-factor instrumental leadership model, which explains incremental variance in leader outcomes in over and above transactional and transformational leadership.

Nonlinear analysis of human physical activity patterns in health and disease.

The reliable and objective assessment of chronic disease state has been and still is a very significant challenge in clinical medicine. An essential feature of human behavior related to the health status, the functional capacity, and the quality of life is the physical activity during daily life. A common way to assess physical activity is to measure the quantity of body movement. Since human activity is controlled by various factors both extrinsic and intrinsic to the body, quantitative parameters only provide a partial assessment and do not allow for a clear distinction between normal and abnormal activity. In this paper, we propose a methodology for the analysis of human activity pattern based on the definition of different physical activity time series with the appropriate analysis methods. The temporal pattern of postures, movements, and transitions between postures was quantified using fractal analysis and symbolic dynamics statistics. The derived nonlinear metrics were able to discriminate patterns of daily activity generated from healthy and chronic pain states.

Two Signatures For A New Blood-Based Test For Colorectal Cancer Screening

Background: Detection rates for adenoma and early colorectal cancer (CRC) are unsatisfactory due to low compliance towards invasive screening procedures such as colonoscopy. There is a large unmet screening need calling for an accurate, non-invasive and cost-effective test to screen for early neoplastic and pre-neoplastic lesions. Our goal is to identify effective biomarker combinations to develop a screening test aimed at detecting precancerous lesions and early CRC stages, based on a multigene assay performed on peripheral blood mononuclear cells (PBMC).Methods: A pilot study was conducted on 92 subjects. Colonoscopy revealed 21 CRC, 30 adenomas larger than 1 cm and 41 healthy controls. A panel of 103 biomarkers was selected by two approaches: a candidate gene approach based on literature review and whole transcriptome analysis of a subset of this cohort by Illumina TAG profiling. Blood samples were taken from each patient and PBMC purified. Total RNA was extracted and the 103 biomarkers were tested by multiplex RT-qPCR on the cohort. Different univariate and multivariate statistical methods were applied on the PCR data and 60 biomarkers, with significant p-value (< 0.01) for most of the methods, were selected.Results: The 60 biomarkers are involved in several different biological functions, such as cell adhesion, cell motility, cell signaling, cell proliferation, development and cancer. Two distinct molecular signatures derived from the biomarker combinations were established based on penalized logistic regression to separate patients without lesion from those with CRC or adenoma. These signatures were validated using bootstrapping method, leading to a separation of patients without lesion from those with CRC (Se 67%, Sp 93%, AUC 0.87) and from those with adenoma larger than 1cm (Se 63%, Sp 83%, AUC 0.77). In addition, the organ and disease specificity of these signatures was confirmed by means of patients with other cancer types and inflammatory bowel diseases.Conclusions: The two defined biomarker combinations effectively detect the presence of CRC and adenomas larger than 1 cm with high sensitivity and specificity. A prospective, multicentric, pivotal study is underway in order to validate these results in a larger cohort.

¿Cómo hacer un análisis cuantitativo de datos de tipo descriptivo con el paquete estadístico SPSS?

En la actualidad es difícil hablar de procesos estadísticos de análisis cuantitativo de datos sin hacer referencia a la informática aplicada a la investigación. Estos recursos informáticos se basan a menudo en paquetes de programas informáticos que tienen por objetivo ayudar al/la investigador/a en la fase de análisis de datos. En estos momentos uno de los paquetes más perfeccionados y completos es el SPSS (Statistical Package for the Social Sciences). El SPSS es un paquete de programas para llevar a cabo el análisis estadístico de los datos. Constituye una aplicación estadística muy potente, de la que se han ido desarrollando diversas versiones desde sus inicios, en los años setenta. En esta ficha las salidas de ordenador que se presentan corresponden a la versión 11.0.1. No obstante, aunque la forma ha ido variando desde sus inicios, su funcionamiento sigue siendo muy similar entre las diferentes versiones. Antes de iniciarnos en la utilización de las aplicaciones del SPSS es importante familiarizarse con algunas de las ventanas que más usaremos. Al entrar al SPSS lo primero que nos encontramos es el editor de datos. Esta ventana visualiza, básicamente, los datos que iremos introduciendo. El editor de datos incluye dos opciones: la vista de los datos y la de las variables. Estas opciones pueden seleccionarse a partir de las dos pestañas que se presentan en la parte inferior. La vista de datos contiene el menú general y la matriz de datos. Esta matriz está estructurada ubicando los casos en las filas y las variables en las columnas.

Random assignment of intervention points in two phase single-case designs: data-division-specific distributions

The present study explores the statistical properties of a randomization test based on the random assignment of the intervention point in a two-phase (AB) single-case design. The focus is on randomization distributions constructed with the values of the test statistic for all possible random assignments and used to obtain p-values. The shape of those distributions is investigated for each specific data division defined by the moment in which the intervention is introduced. Another aim of the study consisted in testing the detection of inexistent effects (i.e., production of false alarms) in autocorrelated data series, in which the assumption of exchangeability between observations may be untenable. In this way, it was possible to compare nominal and empirical Type I error rates in order to obtain evidence on the statistical validity of the randomization test for each individual data division. The results suggest that when either of the two phases has considerably less measurement times, Type I errors may be too probable and, hence, the decision making process to be carried out by applied researchers may be jeopardized.

R functions for quantifying nonindependence in standard dyadic and SRM designs

Interdependence is the main feature of dyadic relationships and, in recent years, various statistical procedures have been proposed for quantifying and testing this social attribute in different dyadic designs. The purpose of this paper is to develop several functions for this kind of statistical tests in an R package, known as nonindependence, for use by applied social researchers. A Graphical User Interface (GUI) is also developed to facilitate the use of the functions included in this package. Examples drawn from psychological research and simulated data are used to illustrate how the software works.

An overall statistic for testing symmetry in social interactions

The present work focuses the attention on the skew-symmetry index as a measure of social reciprocity. This index is based on the correspondence between the amount of behaviour that each individual addresses to its partners and what it receives from them in return. Although the skew-symmetry index enables researchers to describe social groups, statistical inferential tests are required. The main aim of the present study is to propose an overall statistical technique for testing symmetry in experimental conditions, calculating the skew-symmetry statistic (Φ) at group level. Sampling distributions for the skew- symmetry statistic have been estimated by means of a Monte Carlo simulation in order to allow researchers to make statistical decisions. Furthermore, this study will allow researchers to choose the optimal experimental conditions for carrying out their research, as the power of the statistical test has been estimated. This statistical test could be used in experimental social psychology studies in which researchers may control the group size and the number of interactions within dyads.

Agreement in interpersonal perception as a predictor of group performance

The present work deals with quantifying group characteristics. Specifically, dyadic measures of interpersonal perceptions were used to forecast group performance. 46 groups of students, 24 of four and 22 of five people, were studied in a real educational assignment context and marks were gathered as an indicator of group performance. Our results show that dyadic measures of interpersonal perceptions account for final marks. By means of linear regression analysis 85% and 85.6% of group performance was respectively explained for group sizes equal to four and five. Results found in the scientific literature based on the individualistic approach are no larger than 18%. The results of the present study support the utility of dyadic approaches for predicting group performance in social contexts.

Some common indexes of group diversity: upper boundaries

Workgroup diversity can be conceptualized as variety, separation, or disparity. Thus, the proper operationalization of diversity depends on how a diversity dimension has been defined. Analytically, the minimal diversity must be obtained when there are no differences on an attribute among the members of a group, however maximal diversity has a different shape for each conceptualization of diversity. Previous work on diversity indexes indicated maximum values for variety (e.g., Blau"s index and Teachman"s index), separation (e.g., standard deviation and mean Euclidean distance), and disparity (e.g., coefficient of variation and the Gini coefficient of concentration), although these maximum values are not valid for all group characteristics (i.e., group size and group size parity) and attribute scales (i.e., number of categories). We demonstrate analytically appropriate upper boundaries for conditional diversity determined by some specific group characteristics, avoiding the bias related to absolute diversity. This will allow applied researchers to make better interpretations regarding the relationship between group diversity and group outcomes.

Aplicación de las técnicas de suavizado en la variación negativa contingente (CNV)

El presente trabajo recoge de forma breve laproblemática de la estimación de la serial en series temporales de datos obtenidos en registros ERP. Se centra en aquellos componentes de frecuencia mis baja, como es el caso de la CNV: Sepropone la utilización alternativa de las técnicas de suavizado del Análisis Exploratorio de Datos (EDA), para mejorar la estimación obtenida, en comparación con la técnica del promediado simple de diferentes ensayos.

A road map toward a globally harmonized approach for occupational health surveillance and epidemiology in nanomaterial workers

OBJECTIVE: Few epidemiological studies have addressed the health of workers exposed to novel manufactured nanomaterials. The small current workforce will necessitate pooling international cohorts. METHOD: A road map was defined for a globally harmonized framework for the careful choice of materials, exposure characterization, identification of study populations, definition of health endpoints, evaluation of appropriateness of study designs, data collection and analysis, and interpretation of the results. RESULTS: We propose a road map to reach global consensus on these issues. The proposed strategy should ensure that the costs of action are not disproportionate to the potential benefits and that the approach is pragmatic and practical. CONCLUSIONS: We should aim to go beyond the collection of health complaints, illness statistics, or even counts of deaths; the manifestation of such clear endpoints would indicate a failure of preventive measures.

Tratamiento multivariado de subpoblaciones en una gran encuesta social: la construcción de zonas sociales

Cuando se realiza una encuesta social en un amplio territorio queda siempre el deseo de aplicar análisis similares a los realizados en la encuesta a poblaciones o territorios más reducidos, evidentemente utilizando los propios datos de la encuesta. El objetivo de este articulo consiste en mostrar cómo cada estrato de una muestra estratificada puede constituir una base muestral para llevar a cabo dichos análisis con todas las garantías de precisión o, al menos, con garantías calculables y aceptables sin aumentar el número muestral para la encuesta general.

Heavy metal accumulation by intestinal helminths of vertebrates

The relevancy of parasites as potential indicators of environmental quality has been increasing over the last years, mostly due to the variety of ways in which they respond to anthropogenic pollution. The use of fish parasites as bioindicators of heavy metal pollution in aquatic ecosystems has been widely studied. However, little information concerning terrestrial habitats is presently available. In fact, in the last two decades several studies have been performed worldwide in different habitats and/or conditions (theoretically both in polluted and unpolluted terrestrialecosystems, but mainly in aquatic ecosystems) in order to investigate heavy metal pollution using parasitological models. Different groups of vertebrates (mainly fish, mammals and birds) and several parasitological models have been tested involving acanthocephalans mostly, but also cestodes and nematodes. It is not the aim of this chapter to do a complete revision of the availabledata concerning this subject. Instead, we emphasize some general aspects and compile a mini-review of the work performed in this field by our research group. The results obtained until now allow confirming several parasitic models as promising bioindicator systems to evaluate environmental cadmium and mainly lead pollution in terrestrial non-urban habitats, as it was already demonstrated for aquatic ecosystems. The present knowledge also allows confirming that parasites can reveal environmental impact. Environmental parasitology is an interdisciplinary field, which needs simultaneous expertise from toxicology, environmental chemistry and parasitology. Furthermore, environmental parasitology should be taken into account in order to increase the efficiency of environmental monitoring programs.