911 resultados para added variable plot
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Two groundwater bodies, Grazer Feld and Leibnitzer Feld, with surface areas of 166 and 103 km2 respectively are characterised for the first time by measuring the combination of d18O/d2H, 3H/3He, 85Kr, CFC-11, CFC-12 and hydrochemistry in 34 monitoring wells in 2009/2010. The timescales of groundwater recharge have been characterised by 131 d18O measurements of well and surface water sampled on a seasonal basis. Most monitoring wells show a seasonal variation or indicate variable contributions of the main river Mur (0–30%, max. 70%) and/or other rivers having their recharge areas in higher altitudes. Combined d18O/d2H-measurements indicate that 65–75% of groundwater recharge in the unusual wet year of 2009 was from precipitation in the summer based on values from the Graz meteorological station. Monitoring wells downstream of gravel pit lakes show a clear evaporation trend. A boron–nitrate differentiation plot shows more frequent boron-rich water in the more urbanised Grazer Feld and more frequent nitrate-rich water in the more agricultural used Leibnitzer Feld indicating that a some of the nitrate load in the Grazer Feld comes from urban sewer water. Several lumped parameter models based on tritium input data from Graz and monthly data from the river Mur (Spielfeld) since 1977 yield a Mean Residence Time (MRT) for the Mur-water itself between 3 and 4 years in this area. Data from d18O, 3H/3He measurements at the Wagna lysimeter station supports the conclusion that 90% of the groundwaters in the Grazer Feld and 73% in the Leibnitzer Feld have MRTs of <5 years. Only in a few groundwaters were MRTs of 6–10 or 11–25 years as a result of either a long-distance water inflow in the basins or due to longer flow path in somewhat deeper wells (>20 m) with relative thicker unsaturated zones. The young MRT of groundwater from two monitoring wells in the Leibnitzer Feld was confirmed by 85Kr-measurements. Most CFC-11 and CFC-12 concentrations in the groundwater exceed the equilibration concentrations of modern concentrations in water and are therefore unsuitable for dating purposes. An enrichment factor up to 100 compared to atmospheric equilibrium concentrations and the obvious correlation of CFC-12 with SO4, Na, Cl and B in the ground waters of the Grazer Feld suggest that waste water in contact with CFC-containing material above and below ground is the source for the contamination. The dominance of very young groundwater (<5 years) indicates a recent origin of the contamination by nitrate and many other components observed in parts of the groundwater bodies. Rapid measures to reduce those sources are needed to mitigate against further deterioration of these waters.
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Two factors that have been suggested as key in explaining individual differences in fluid intelligence are working memory and sensory discrimination ability. A latent variable approach was used to explore the relative contributions of these two variables to individual differences in fluid intelligence in middle to late childhood. A sample of 263 children aged 7–12 years was examined. Correlational analyses showed that general discrimination ability (GDA)and working memory (WM) were related to each other and to fluid intelligence. Structural equation modeling showed that within both younger and older age groups and the sample as a whole, the relation between GDA and fluid intelligence could be accounted for by WM. While WM was able to predict variance in fluid intelligence above and beyond GDA, GDA was not able to explain significant amounts of variance in fluid intelligence, either in the whole sample or within the younger or older age group. We concluded that compared to GDA, WM should be considered the better predictor of individual differences in fluid intelligence in childhood. WM and fluid intelligence, while not being separable in middle childhood, develop at different rates, becoming more separable with age.
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addplot adds twoway plot objects to an existing twoway graph. This is useful if you want to add additional objects such as titles or extra data points to a twoway graph after it has been created. Most of what addplot can do, can also be done by rerunning the original graph command including additional options or plot statements. addplot, however, might be useful if you have to modify a graph for which you cannot rerun the original command, for example, because you only have the graph file but not the data that were used to create the graph. Furthermore, addplot can do certain things that would be difficult to achieve in a single graph command (e.g. customizing individual subgraphs within a by-graph). addplot also provides a substitute for some of the functionality of the graph editor.
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by E. H. Lindo
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Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.
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by Michael Josephs
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by Samuel Lee
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Theory: Interpersonal factors play a major role in causing and maintaining depression. It is unclear, however, to what degree significant others of the patient need to be involved for characterizing the patient's interpersonal style. Therefore, our study sought to investigate how impact messages as perceived by the patients' significant others add to the prediction of psychotherapy process and outcome above and beyond routine assessments, and therapist factors. Method: 143 outpatients with major depressive disorder were treated by 24 therapists with CBT or Exposure-Based Cognitive Therapy. Interpersonal style was measured pre and post therapy with the informant‐based Impact Message Inventory (IMI), in addition to the self‐report Inventory of Interpersonal Problems (IIP‐32). Indicators for the patients' dominance and affiliation as well as interpersonal distress were calculated from these measures. Depressive and general symptomatology was assessed at pre, post, and at three months follow‐up, and by process measures after every session. Results: Whereas significant other's reports did not add significantly to the prediction of the early therapeutic alliance, central mechanisms of change, or post‐therapy outcome including therapist factors, the best predictor of outcome 3 months post therapy was an increase in dominance as perceived by significant others. Conclusions: The patients' significant others seem to provide important additional information about the patients' interpersonal style and therefore should be included in the diagnostic process. Moreover, practitioners should specifically target interpersonal change as a potential mechanism of change in psychotherapy for depression.
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Demonstration of survival and outcome of progressive multifocal leukoencephalopathy (PML) in a 56-year-old patient with common variable immunodeficiency, consisting of severe hypogammaglobulinemia and CD4+ T lymphocytopenia, during continuous treatment with mirtazapine (30 mg/day) and mefloquine (250 mg/week) over 23 months. Regular clinical examinations including Rankin scale and Barthel index, nine-hole peg and box and block tests, Berg balance, 10-m walking tests, and Montreal Cognitive Assessment (MoCA) were done. Laboratory diagnostics included complete blood count and JC virus (JCV) concentration in cerebrospinal fluid (CSF). The noncoding control region (NCCR) of JCV, important for neurotropism and neurovirulence, was sequenced. Repetitive MRI investigated the course of brain lesions. JCV was detected in increasing concentrations (peak 2568 copies/ml CSF), and its NCCR was genetically rearranged. Under treatment, the rearrangement changed toward the archetype sequence, and later JCV DNA became undetectable. Total brain lesion volume decreased (8.54 to 3.97 cm(3)) and atrophy increased. Barthel (60 to 100 to 80 points) and Rankin (4 to 2 to 3) scores, gait stability, and box and block (7, 35, 25 pieces) and nine-hole peg (300, 50, 300 s) test performances first improved but subsequently worsened. Cognition and walking speed remained stable. Despite initial rapid deterioration, the patient survived under continuous treatment with mirtazapine and mefloquine even though he belongs to a PML subgroup that is usually fatal within a few months. This course was paralleled by JCV clones with presumably lower replication capability before JCV became undetectable. Neurological deficits were due to PML lesions and progressive brain atrophy.
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The time variable Earth’s gravity field contains information about the mass transport within the system Earth, i.e., the relationship between mass variations in the atmosphere, oceans, land hydrology, and ice sheets. For many years, satellite laser ranging (SLR) observations to geodetic satellites have provided valuable information of the low-degree coefficients of the Earth’s gravity field. Today, the Gravity Recovery and Climate Experiment (GRACE) mission is the major source of information for the time variable field of a high spatial resolution. We recover the low-degree coefficients of the time variable Earth’s gravity field using SLR observations up to nine geodetic satellites: LAGEOS-1, LAGEOS-2, Starlette, Stella, AJISAI, LARES, Larets, BLITS, and Beacon-C. We estimate monthly gravity field coefficients up to degree and order 10/10 for the time span 2003–2013 and we compare the results with the GRACE-derived gravity field coefficients. We show that not only degree-2 gravity field coefficients can be well determined from SLR, but also other coefficients up to degree 10 using the combination of short 1-day arcs for low orbiting satellites and 10-day arcs for LAGEOS-1/2. In this way, LAGEOS-1/2 allow recovering zonal terms, which are associated with long-term satellite orbit perturbations, whereas the tesseral and sectorial terms benefit most from low orbiting satellites, whose orbit modeling deficiencies are minimized due to short 1-day arcs. The amplitudes of the annual signal in the low-degree gravity field coefficients derived from SLR agree with GRACE K-band results at a level of 77 %. This implies that SLR has a great potential to fill the gap between the current GRACE and the future GRACE Follow-On mission for recovering of the seasonal variations and secular trends of the longest wavelengths in gravity field, which are associated with the large-scale mass transport in the system Earth.
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We propose a nonparametric variance estimator when ranked set sampling (RSS) and judgment post stratification (JPS) are applied by measuring a concomitant variable. Our proposed estimator is obtained by conditioning on observed concomitant values and using nonparametric kernel regression.
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When genetic constraints restrict phenotypic evolution, diversification can be predicted to evolve along so-called lines of least resistance. To address the importance of such constraints and their resolution, studies of parallel phenotypic divergence that differ in their age are valuable. Here, we investigate the parapatric evolution of six lake and stream threespine stickleback systems from Iceland and Switzerland, ranging in age from a few decades to several millennia. Using phenotypic data, we test for parallelism in ecotypic divergence between parapatric lake and stream populations and compare the observed patterns to an ancestral-like marine population. We find strong and consistent phenotypic divergence, both among lake and stream populations and between our freshwater populations and the marine population. Interestingly, ecotypic divergence in low-dimensional phenotype space (i.e. single traits) is rapid and seems to be often completed within 100 years. Yet, the dimensionality of ecotypic divergence was highest in our oldest systems and only there parallel evolution of unrelated ecotypes was strong enough to overwrite phylogenetic contingency. Moreover, the dimensionality of divergence in different systems varies between trait complexes, suggesting different constraints and evolutionary pathways to their resolution among freshwater systems.