Abundance of mesozooplankton in the western part of the Black Sea in autumn 1999 during the National Monitoring Programme

The dataset is based on samples collected in the summer of 1999 in the Western Black Sea in front of Bulgaria coast. The whole dataset is composed of 59 samples (from 24 stations of National Monitoring Grid) with data of mesozooplankton species composition abundance and biomass. Samples were collected in discrete layers 0-10, 0-20, 0-50, 10-25, 25-50, 50-100 and from bottom up to the surface at depths depending on water column stratification and the thermocline depth. The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).

Abundance of mesozooplankton in the western part of the Black Sea in spring 1997 during the National Monitoring Programme

The "15BO1997001" dataset is based on samples collected in the spring of 1997. The whole dataset is composed of 66 samples (from 27 stations of National Monitoring Sampling Grid) with data of zooplankton species composition, abundance and biomass. Samples were collected in discrete layers 0-10, 0-20, 0-50, 10-25, 25-50, 50-100 and from bottom up to the surface at depths depending on water column stratification and the thermocline depth. Zooplankton samples were collected with vertical closing Juday net,diameter - 36cm, mesh size 150 µm. Tows were performed from surface down to bottom meters depths in discrete layers. Samples were preserved by a 4% formaldehyde sea water buffered solution. Sampling volume was estimated by multiplying the mouth area with the wire length. Mesozooplankton abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). Taxon-specific abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Lyudmila Kamburska using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).

Abundance of mesozooplankton in the western part of the Black Sea in spring 2002 during the National Monitoring Programme of the Bulgarian Institute of Oceanography

The dataset is based on samples collected in the spring of 2002 in the Western Black Sea in front of Bulgaria coast. The whole dataset is composed of 76 samples (from 27 stations of National Monitoring Grid) with data of mesozooplankton species composition abundance and biomass. Sampling on zooplankton was performed from bottom up to the surface at depths depending on water column stratification and the thermocline depth. Zooplankton samples were collected with vertical closing Juday net,diameter - 36cm, mesh size 150 µm. Tows were performed from surface down to bottom meters depths in discrete layers. Samples were preserved by a 4% formaldehyde sea water buffered solution. Sampling volume was estimated by multiplying the mouth area with the wire length. Mesozooplankton abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Kremena Stefanova using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972). Taxon-specific abundance: The collected material was analysed using the method of Domov (1959). Samples were brought to volume of 25-30 ml depending upon zooplankton density and mixed intensively until all organisms were distributed randomly in the sample volume. After that 5 ml of sample was taken and poured in the counting chamber which is a rectangle form for taxomomic identification and count. Copepods and Cladoceras were identified and enumerated; the other mesozooplankters were identified and enumerated at higher taxonomic level (commonly named as mesozooplankton groups). Large (> 1 mm body length) and not abundant species were calculated in whole sample. Counting and measuring of organisms were made in the Dimov chamber under the stereomicroscope to the lowest taxon possible. Taxonomic identification was done at the Institute of Oceanology by Kremena Stefanova using the relevant taxonomic literature (Mordukhay-Boltovskoy, F.D. (Ed.). 1968, 1969,1972).

Industrial Clusters in India: Evidence from Automobile Clusters in Chennai and the National Capital Region

This study analyzes the patterns of agglomeration of some modern manufacturing sectors in India, and in particular the Indian automobile sector. It also examines and contrasts the factors that have led to different patterns of cluster development in two leading auto clusters in India-Chennai and the National Capital Region (NCR). Moreover, the study analyzes whether firms in clusters perform better than those that are excluded and whether the relative importance of variables that determine the behavior of firms differs among clusters. Our analyses, which employ a combination of quantitative and qualitative methods, show that Indian industrial clusters are largely concentrated in the three clustered regions: NCR, Mumbai-Pune, and Chennai-Bangalore, across different manufacturing sectors. Our study of the auto clusters in Chennai and the NCR find considerable differences in the patterns of cluster formation, due partly to the historical and policy conditions under which firms, particularly, the lead firms must operate. Moreover, our econometric analyses confirmed that being part of a cluster positively influences the performance of the auto component firms and those belonging to a cluster perform better.

Kenya after the 2007 "post-election violence" : constitutional reform and the National Accord and Reconciliation Act

Immediately after the announcement of the re-election of President Kibaki on the evening of 30 December 2007, Kenya was thrust into the worst civil unrest experienced by the country since independence – a development that became known as the "Post-Election Violence" (PEV). However, after a subsequent process of reconciliation, the PEV came to an end within a relatively short period. The present-day politics of Kenya are being conducted within the framework of a provisional Constitution that took shape through peaceful mediation. How did Kenya manage to put a lid on a period of turmoil that placed the country in unprecedented danger? This paper traces the sequence of events that led to mediation, explains the emergency measures that were needed to maintain law and order, and indicates the remaining problems that still need to be solved.

Analysis and comparison of the national and regional emission inventories for the Greater Madrid Region through air quality simulations

Este trabajo presenta un análisis y una metodología para la armonización de inventarios de emisiones utilizados en modelos de calidad del aire.

Interaction between karstic aquifers and allogenic rivers: the aquifer of the national park of the ephemeral river Lobos Canyon (Spain)

A methodology is described for understanding the interaction of karstic aquifers with allogenic rivers, where little information is available. This methodology includes conventional hydrogen- ology methods tracer tests and measurements of flow into, out of and circulating within the karstic system. The method is designed to un- derstand the hydrogeological behaviour of a river in sufficient detail, given a short study pe- riod. The methodology is applied to a karstic system in Spain, obtaining useful, quantitative results for a hydrological year, such as an esti- mate of the water balance, differentiation be- tween autogenic and allogenic natural recharge, relationship and connection between the river and the aquifer, and measurements of infiltration capacity in watercourses under different hydro- logical situations. The paper deals with a useful example that could be applied to other rivers and aquifers where few data are available. It can be applied to aquifers under a natural regime and Mediterranean climate.

The national estuarine pollution study : a report to the Congress.

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The national estuarine pollution study : a report to the Congress.

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The national estuarine pollution study : a report to the Congress.

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Database resources of the National Center for Biotechnology Information

In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources that operate on the data in GenBank and a variety of other biological data made available through NCBI’s Web site. NCBI data retrieval resources include Entrez, PubMed, LocusLink and the Taxonomy Browser. Data analysis resources include BLAST, Electronic PCR, OrfFinder, RefSeq, UniGene, HomoloGene, Database of Single Nucleotide Polymorphisms (dbSNP), Human Genome Sequencing, Human MapViewer, GeneMap’99, Human–Mouse Homology Map, Cancer Chromosome Aberration Project (CCAP), Entrez Genomes, Clusters of Orthologous Groups (COGs) database, Retroviral Genotyping Tools, Cancer Genome Anatomy Project (CGAP), SAGEmap, Gene Expression Omnibus (GEO), Online Mendelian Inheri­tance in Man (OMIM), the Molecular Modeling Database (MMDB) and the Conserved Domain Database (CDD). Augmenting many of the Web applications are custom implementations of the BLAST program optimized to search specialized data sets. All of the resources can be accessed through the NCBI home page at: http://www.ncbi.nlm.nih.gov.

New Members and Foreign Associates Elected to the National Academy of Sciences on May 1, 2001: 72 New Members Chosen by the Academy

The Academy has elected 72 new members and 15 foreign associates from 10 countries in recognition of their distinguished and continuing achievements in original research. The election was held during the business session of the 138th annual meeting of the Academy. Election to membership in the Academy is considered one of the highest honors that can be accorded a U.S. scientist or engineer. Foreign associates are non-voting members of the Academy, with citizenship outside of the United States.

Potentials of the National Corn Genome Initiative

The present paper summarizes future needs in information and tools, technology, infrastructure, training, funding, and bioinformatics, to provide the genomic knowledge and tools for breeding and biotechnological goals in maize. The National Corn Genome Initiative (NCGA) has developed through actions taken by the National Corn Growers Association (NCGA) and participation in a planning process by institutions, companies, and organizations. At the web address for the NCGI, http://www.inverizon.com/ncgi, are detailed analyses of goals and costs, impact and value, and strategy and approaches. The NCGI has also produced an informative and perceptive video suitable for public groups or schools, about agricultural contributions to life and the place of maize in these contributions. High potential can be expected, from cross-application of knowledge obtained in maize and other cereals. Development of information and tools for all crops, whether monocots or dicots, will be gained through an initiative, and each crop will be positioned to advance with cost-effective parallels, especially for expressed sequences, markers, and physical mapping.