Condition index and percentage edibility of Crassostrea madrasensis (Preston) inhabiting the Cochin Harbour

Monthly variations in condition index and percentage edibility of the population of oysters, namely, Crassostrea madrasensis (Preston) is reported for males, females and indeterminates for the period October 1981 to September 1982. Condition index and percentage edibility showed more or less similar trend for the total population and also for males, females and indeterminates. The condition index and percentage edibility were maximum during October 1981 which declined progressively and reached the lowest in February-March, 1982. From April it showed steady increase and reached the maximum again in October 1982 and this coincided with the gonadal cycle in oysters.

A statistical index of growth condition in an aquaculture experiment

A simple statistical index, for evaluating the condition of growth in an aquaculture experiment and indicating the extent of effect of any plausible rival hypothesis, is presented.

Trophic State Index, morphoedaphic index and fish yield prediction in a sub-tropical lake, Manchar (Sindh), Pakistan

Limnological factors of a sub-tropical lake Manchar were studied on seasonal basis. The mean values of various parameters were: transparency, (secchi disc reading): 90.5 cm, Orthophosphate: 0.257 mg/l, TDS: 3310,5 mg/l, Conductivity: 5232 µs/l, Total Chlorophyll (Planktonic): 31.3 µg/l Planktonic biomass: 5466 µg/l. Trophic state index (TSI) was calculated by using Carlson's (1977) equations. Mean TSI for transparency was 61, while for orthophosphate and chlorophyll, it was 82 and 64 respectively. TSI values indicate advanced eutrophic state of Manchar Lake. Morphoedaphic index (MEI) was also calculated on seasonal basis. The mean values were, TDS: 1103, conductivity: 1744, alkalinity: 60, transparency: 29 and biomass (plankton dry weight): 1746. Fish yield prediction for Manchar Lake (Z =3m, mean area=100 km²) was calculated by using MEI values. The results were quite different among various parameters. Conductivity (89.1mt/y), biomass (67.6 mt/y) and TDS (44.6 mt/y) were found to be good predictors of fish yield. Chlorophyll, transparency and alkalinity values gave very low estimate.

Water quality assessment of Sonbolrood River by using hylsenhof index

This research investigates the quality of sonbolrood river by using Hylsenhof HFBI indicators and identified Macroinvertebrates invertebrates community in the family level. This study took place during 1388-1389 with four sampling season in four stations respectively in the forests of Kalyj kheyl village in Savadkuh (first station), industrial area of Islamabad (second Station), earth dam of Sonbolrood (third station) and the Place crosses Sonbolrood with Babolrood river (fourth Station). Macroinvertebrates invertebrates collected by quantitative sampler of Sorbr and they were isolated in laboratory by loop and they were identified in the family level. Generally, Macroinvertebrates of Sonbolrood river were formed three branches: Arthropods and flat worms and mollusks, including 3 tiers, 6 orders and 14 families that showed the maximum diversity and density in autumn and the least diversity and density in summer at all stations, also the third and fourth stations respectively were highest and lowest diversity and density. The water quality of Sonbolrood river based on the water quality Guide(Hylsenhof) is evaluated with excellent condition for all stations except third station. Sonbolrood river with having high slope, rocky and sandy bed, with self-refining act, completely is a proper ecosystem for aquatic organisms, but it is done due to increased organic matter and sewage factory located in industrial zone in the third station and then the increased water pollution caused by nurturing the water warm fish in the earth dam of Sonbolrood. (because of this, the water quality at third station based on the water quality Guide(Hylsenhof) are evaluated in a fairly good condition) and adding domestic sewages of adjacent villages like Seyedkola village and Shirdarkola caused increased pollution and increased trophy of Macroinvertebrates that are resistant to pollution and affect upon Macroinvertebrates community.

Content Based Integration of Construction Site Images in Architecture, Engineering, Construction, and Facilities Management (AEC/FM) Model based Systems

This book explores the processes for retrieval, classification, and integration of construction images in AEC/FM model based systems. The author describes a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval that have been integrated into a novel method for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks. objects. Therefore, automated methods for the integration of construction images are important for construction information management. During this research, processes for retrieval, classification, and integration of construction images in AEC/FM model based systems have been explored. Specifically, a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval have been deployed in order to develop a methodology for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks.

Content Based Integration of Construction Site Images in AEC/FM Model Based Systems

The Architecture, Engineering, Construction and Facilities Management (AEC/FM) industry is rapidly becoming a multidisciplinary, multinational and multi-billion dollar economy, involving large numbers of actors working concurrently at different locations and using heterogeneous software and hardware technologies. Since the beginning of the last decade, a great deal of effort has been spent within the field of construction IT in order to integrate data and information from most computer tools used to carry out engineering projects. For this purpose, a number of integration models have been developed, like web-centric systems and construction project modeling, a useful approach in representing construction projects and integrating data from various civil engineering applications. In the modern, distributed and dynamic construction environment it is important to retrieve and exchange information from different sources and in different data formats in order to improve the processes supported by these systems. Previous research demonstrated that a major hurdle in AEC/FM data integration in such systems is caused by its variety of data types and that a significant part of the data is stored in semi-structured or unstructured formats. Therefore, new integrative approaches are needed to handle non-structured data types like images and text files. This research is focused on the integration of construction site images. These images are a significant part of the construction documentation with thousands stored in site photographs logs of large scale projects. However, locating and identifying such data needed for the important decision making processes is a very hard and time-consuming task, while so far, there are no automated methods for associating them with other related objects. Therefore, automated methods for the integration of construction images are important for construction information management. During this research, processes for retrieval, classification, and integration of construction images in AEC/FM model based systems have been explored. Specifically, a combination of techniques from the areas of image and video processing, computer vision, information retrieval, statistics and content-based image and video retrieval have been deployed in order to develop a methodology for the retrieval of related construction site image data from components of a project model. This method has been tested on available construction site images from a variety of sources like past and current building construction and transportation projects and is able to automatically classify, store, integrate and retrieve image data files in inter-organizational systems so as to allow their usage in project management related tasks.

Negative index photonic crystal lenses based on carbon nanotube arrays

We report a novel utilization of periodic arrays of carbon nanotubes in the realization of diffractive photonic crystal lenses. Carbon nanotube arrays with nanoscale dimensions (lattice constant 400 nm and tube radius 50 nm) displayed a negative refractive index in the optical regime where the wavelength is of the order of array spacing. A detailed computational analysis of band gaps and optical transmission through the nanotubes based planar, convex and concave shaped lenses was performed. Due to the negative-index these lenses behaved in an opposite fashion compared to their conventional counter parts. A plano-concave lens was established and numerically tested, displaying ultra-small focal length of 1.5 μm (∼2.3 λ) and a near diffraction-limited spot size of 400 nm (∼0.61 λ). © 2012 Elsevier B.V. All rights reserved.