Phytoplankton diversity and chlorophyll-A in a polluted estuary

The quantity of phytoplankton in Newark Bay, New Jersey as indicated by chlorophyll-a content of the water, is low in the winter and early spring, and fluctuates greatly during the spring and summer. Chlorophyll-a concentrations are generally less than 20 μg/l until April. Between April and August, three phytoplankton blooms were indicated by chlorophyll-a concentrations as high as 81.4 μg/l. Net phytoplankton diversity values indicated generally eutrophic conditions; however, there was no significant correlation between diversity and chlorophyll-a concentrations. A role of nannoplankton in blooms is indicated.     

In situ Raman observation of the crystallization in NaNO3–Na2SO4–H2O solution droplets

Several double salts have been detected in building materials and most of these salts are incongruently soluble compounds. In contrast to single salts, however, no systematic investigations of the crystallization behavior and deleterious effects of incongruently soluble double salts exist. To assess the damage potential of these salts, a systematic investigation of their highly complex behavior is desirable. This paper deals with the crystallization behavior of various solids in the ternary mixed NaNO₃–Na₂SO₄ system including the formation of the double salt darapskite, Na₃NO₃SO₄·H₂O. The crystallization sequence during droplet evaporation experiments at room conditions was determined using Raman and polarization microscopy. The basic idea of this research is to use deviations of the crystallization sequence of a salt or a mixed salt solution from the equilibrium pathway as an indicator to detect the degree of supersaturation. The observed crystallization pathway includes the formation of the metastable phases Na₂SO₄(III), Na₂SO₄(V) and darapskite. The experimental observations are discussed on the basis of the NaNO₃–Na₂SO₄–H₂O phase diagram and the results provide evidence for crystal growth from highly supersaturated solutions in both systems. If the crystals growing under these conditions are confined, these supersaturations result in substantial crystallization pressures.     

On the Principle of Least Interaction Action and the Laplacean satellites of Jupiter and Uranus

The Principle of Least Interaction Action, which explains the observed preference in the Solar System for two-satellite resonant configurations, is shown to apply also to the Laplacean satellites of Jupiter and Uranus, in the sense that these triplet resonant structures lie close to configurations for which the time-mean of the action associated with the mutual interaction of the satellites is an overall minimum. Far from the minimum configuration, significant changes take place in the major semi-axes on time-scales ～10⁶-10⁷y. Both systems require times ～10⁸ y to come close to the minimum configuration; to approach resonance to the observed precision of the Laplace relationship (3×10^?4 for the Uranian case, 2×10^?7 for the Jovian case) requires, for both systems, a time closely comparable with the age of the solar system.     

Non-Linear Gravitational Clustering Using the Zel'dovich Approximation

As an alternative to computationally expensive N-body simulations for gravitional clustering, the Zel'dovich approximation (ZA) was studied in 3D, 2D and 1D. Plots of the density contrast were compared against linear theory and the exact solution. The ZA was found to perform very well in the linear regime, better than linear theory, and to give a good approximation well into the non-linear regime. This revised version was published online in July 2006 with corrections to the Cover Date.     

EVKG: An interlinked and interoperable electric vehicle knowledge graph for smart transportation system

Over the past decade, the electric vehicle (EV) industry has experienced unprecedented growth and diversification, resulting in a complex ecosystem. To effectively manage this multifaceted field, we present an EV-centric knowledge graph (EVKG) as a comprehensive, cross-domain, extensible, and open geospatial knowledge management system. The EVKG encapsulates essential EV-related knowledge, including EV adoption, EV supply equipment, and electricity transmission network, to support decision-making related to EV technology development, infrastructure planning, and policy-making by providing timely and accurate information and analysis. To enrich and contextualize the EVKG, we integrate the developed EV-relevant ontology modules from existing well-known knowledge graphs and ontologies. This integration enables interoperability with other knowledge graphs in the Linked Data Open Cloud, enhancing the EVKG's value as a knowledge hub for EV decision-making. Using six competency questions, we demonstrate how the EVKG can be used to answer various types of EV-related questions, providing critical insights into the EV ecosystem. Our EVKG provides an efficient and effective approach for managing the complex and diverse EV industry. By consolidating critical EV-related knowledge into a single, easily accessible resource, the EVKG supports decision-makers in making informed choices about EV technology development, infrastructure planning, and policy-making. As a flexible and extensible platform, the EVKG is capable of accommodating a wide range of data sources, enabling it to evolve alongside the rapidly changing EV landscape.     

Earth observations during space shuttle flight STS‐41: Discovery's mission to planet earth

Abstract

Multi‐temporal ERS‐1 SAR data acquired over a large agricultural region in West Bengal was used to classify kharif crops like rice, jute and sugarcane. Rice crop grown under lowland management practice showed a temporal characteristic. The dynamic range of backscatter was highest for this crop in temporal SAR data. This was used to classify rice using temporal SAR data. Such temporal character was not observed for the other study crops, which may be due to the difference in cultivation practice and crop calendar. Significant increase in backscatter from the ploughed fields was used to derive information on onset and duration of land preparations. Synergistic use of optical remote sensing data and SAR data increased the separability of rice crop from homesteads and permanent vegetation classes.