Alkaline phosphatase activity as a tool for assessing nutritional conditions in the seagrass Posidonia oceanica.(L.) Delile

The effects of experimental phosphorus enrichments on alkaline phosphatase activity (APA) of the seagrass Posidonia oceanica (L.) Delile were tested. Short-term additions (as phosphate, 12 hours, in the laboratory) decreased APA by 18-2896, depending on the plant part considered (roots, young leaves or old leaves). The values of APA after this treatment were well correlated with interna1 phosphorus pools (as P concentration in plant tissues). Long-term additions (as phosphate, added to the sediment, 1 month in situ) decreased APA by 40-75%, also depending on the plant part. We conclude that alkaline phosphatase activity is a good indicator of P deficiency in this seagrass. We used this indicator to assess the P-nutritional status in a series of meadows in the NW Mediterranean, finding a high geographical variability, but correlations between APA and basic features of the meadows (carbonate content of the sediment, organic content of the sediment, shoot density, etc.) were not significant. Consequently, phosphorus deficiency does not seem to be directly related to these descriptors.

Photosynthesis and Rubisco kinetics in spring wheat and meadow fescue under conditions of simulated climate change with elevated CO[sub 2] and increased temperatures

Selostus: Kevätvehnän ja nurminadan fotosynteesi ja Rubisco-kinetiikka simuloidun ilmastonmuutoksen eli kohotetun hiilidioksidipitoisuuden ja kohotetun lämpötilan oloissa

Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

An inventory of the marine and transitional Middle/Upper Eocene deposits of the Southeastern Pyrenean Foreland Basin (NE Spain)

In the southeastern Ebro Foreland Basin, the marine deposits of Lutetian and Bartonian age show excellent outcrop conditions, with a great lateral and horizontal continuity of lithostratigraphic units. In addition, the rich fossil record -mainly larger foraminifers-, provides biostratigraphic data of regional relevance for the whole Paleogene Pyrenean Basin, that can be used for the Middle Eocene biocorrelation of the western Tethys. This contribution is a sedimentary and biostratigraphic synthesis of the basic outcrops and sections of the Lutetian andBartonian marine and transitional deposits in the southeastern sector of the Ebro Foreland Basin.

Association of working conditions with self-reported work-related symptoms: results from the Swiss dataset of the European Working Conditions Survey

Working conditions are important determinants of health. The aims of this article are to 1) identify working conditions and work characteristics that are associated with workers' perceptions that their work is harmful to their health and 2) identify with what symptoms these working conditions are associated.We used the Swiss dataset from the 2005 edition of the European Working Conditions Survey. The dependent variable was based on the question "Does your work affect your health?". Logistic regression was used to identify a set of variables collectively associated with self-reported work-related adverse health effects.A total of 330 (32%) participants reported having their health affected by work. The most frequent symptoms included backache (17.1%), muscular pains (13.1%), stress (18.3%) and overall fatigue (11.7%). Scores for self-reported exposure to physicochemical risks, postural and physical risks, high work demand, and low social support were all significantly associated with workers' perceptions that their work is harmful to their health, regardless of gender or age. A high level of education was associated with stress symptoms, and reports that health was affected by work was associated with low job satisfaction.Many workers believe that their work affects their health. Health specialists should pay attention to the potential association between work and their patients' health complaints. This is particularly relevant when patients mention symptoms such as muscular pains, backache, overall fatigue, and stress. Specific attention should be given to complaints of stress in highly educated workers.

Albedo and estimates of net radiation for green beans under polyethylene cover and field conditions

This paper describes the albedo (r) and estimates of net radiation and global solar irradiance for green beans crop (Phaseolus vulgaris L.), cultivated in greenhouse with cover of polyethylene and field conditions, in Botucatu, SP, Brazil (22º 54' S; 48º 27' W; 850 m). The solar global irradiance (Rg) and solar reflected radiation (Rr) were used to estimate the albedo through the ratio between Rr and Rg. The diurnal curves of albedo were obtained for days with clear sky and partially cloudy conditions, for different phenological stages of the crop. The albedo ranged with the solar elevation, the environment and the phenological stages. The cloudiness range have almost no influence on the albedo diurnal amount. The estimation of radiation were made by linear regression, using the global solar irradiance (Rg) and net short-waves radiation (Rc) as independent variables. All estimates of radiation showed better adjustment for specific phenological periods compared to the entire crop growing cycle. The net radiation in the greenhouse has been estimated by the global solar irradiance measured at field conditions.

Reinforced Earth and Stone Columns for Weak Subsoil Conditions, HR-510, 1980

Reinforced Earth is a French development that has been used in the United States for approximately ten years. Virbro-Replacement, more commonly referred to as stone columns, is an outgrowth of deep densification of cohesionless soils originally developed in Germany. Reinforced Earth has applicability when wall height is greater than about twelve feet and deep seated foundation failure is not a concern. Stone columns are applicable when soft, cohesive subsoil conditions are encountered and bearing capacity and shearing resistance must be increased. The conditions in Sioux City on Wesley Way can be summarized as: (1) restricted right of way, (2) fill height in excess of 25 feet creating unstable conditions, (3) adjacent structures that could not be removed. After analyzing alternatives, it was decided that Reinforced Earth walls constructed on top of stone columns were the most practical approach.

Effects of anomalous propagation conditions on weather radar observations

In this chapter our objective is to provide an overview of the effects of anomalous propagation conditions on weather radar observations, based mostly on studies performed by the authors during the last decade, summarizing results from recent publications, presentations, or unpublished material. We believe this chapter may be useful as an introductory text for graduate students, or researchers and practitioners dealing with this topic. Throughout the text a spherical symmetric atmosphere is assumed and the focus is on the occurrence of ground and sea clutter and subsequent problems for weather radar applications. Other related topics such as long-path, over-the-horizon propagation and detection of radar targets (either clutter or weather systems) at long ranges is not considered here; however readers should be aware of the potential problems these phenomena may have as range aliasing may cause these echoes appear nearer than they are ¿ for more details see the discussion about second trip echoes by Zrnic, this volume.