Rice-fish culture: status and potential for increased production in the southwestern states of India

The scope of increasing production through rice-fish integration, suitable for coastal districts of Kerala, Karnataka, Goa and Maharashtra, is reviewed. The method of adopting the lowlying freshwater rice fields to raise 2 rice crops along with 4-species fish culture, followed by a third non-cereal summer crop in a year, is discussed. A calendar of operation and economics of the system are presented.

Simple model of electronic density of states of graphite and its application to the investigation of superlattices

A model of graphite which is easy to comprehend and simple to implement for the simulation of scanning tunneling microscopy (STM) images is described. This model simulates the atomic density of graphite layers, which in turn correlates with the local density of states. The mechanism and construction of such a model is explained with all the necessary details which have not been explicitly reported before. This model is applied to the investigation of rippling fringes which have been experimentally observed on a superlattice, and it is found that the rippling fringes are not related to the superlattice itself. A superlattice with abnormal topmost layers interaction is simulated, and the result affirms the validity of the moiré rotation pattern assumption. The "odd-even" transition along the atomic rows of a superlattice is simulated, and the simulation result shows that when there is more than one rotated layer at the top, the "odd-even" transition will not be manifest. ©2005 The Japan Society of Applied Physics.

Glucocorticoid receptor and protein/RNA synthesis-dependent mechanisms underlie the control of synaptic plasticity by stress

Learning and memory are exquisitely sensitive to behavioral stress, but the underlying mechanisms are still poorly understood. Because activity-dependent persistent changes in synaptic strength are believed to mediate memory processes in brain areas such as the hippocampus we have examined the means by which stress affects synaptic plasticity in the CA1 region of the hippocampus of anesthetized rats, Inescapable behavioral stress (placement on an elevated platform for 30 min) switched the direction of plasticity, favoring low frequency stimulation-induced decreases in synaptic transmission (long-term depression, LTD), and opposing the induction of long-term potentiation by high frequency stimulation, We have discovered that glucocorticoid receptor activation mediates these effects of stress on LTD and longterm potentiation in a protein synthesis-dependent manner because they were prevented by the glucocorticoid receptor antagonist RU 38486 and the protein synthesis inhibitor emetine. Consistent with this, the ability of exogenously applied corticosterone in non-stressed rats to mimic the effects of stress on synaptic plasticity was also blocked by these agents, The enablement of low frequency stimulation-induced LTD by both stress and exogenous corticosterone was also blocked by the transcription inhibitor actinomycin D, Thus, naturally occurring synaptic plasticity is liable to be reversed in stressful situations via glucocorticoid receptor activation and mechanisms dependent on the synthesis of new protein and RNA, This indicates that the modulation of hippocampus-mediated learning by acute inescapable stress requires glucocorticoid receptor-dependent initiation of transcription and translation.

Management of water hyacinth, Eichhornia crassipes, in Lake Victoria Basin

Water hyacinth is a free-floating waterweed native to the Amazon River Basin in South America. In its native range, water hyacinth is not an environmental problem, although the weed is one of the most invasive alien plants in freshwater environments. Water hyacinth has the potential to become invasive through fast vegetative reproduction and rapid growth to accumulate huge biomass and extensive cover in freshwater environments. Over the last 150 years water hyacinth has invaded most countries in the tropics and sub-tropics, introduced by man, mainly for ornamental purposes. Such introductions led to the infestation of most freshwater-ways in the southern United States of America, parts of Australia, the pacific islands, and most countries in Asia and Africa. The extensive tightly packed mats of water hyacinth are often associated with devastating socio-economic and environmental impacts. Invasion by the weed has, therefore, often generated urgent costly problems associated with the weed biomass and its management. A classic example of such problems was triggered by the invasion and proliferation of water hyacinth in the Lake Victoria Basin during the 1980s (Freilink 1989, Taylor 1993, Twongo et al., 1995). The weed infestation marked the beginning of a decade of intensive and systematic campaign by the three riparian states (Kenya, Tanzania and Uganda) to bring weed proliferation under control. The discussions in this Chapter span over ten years of dealing with the challenges paused by the imperative to manage infestations of water hyacinth in the Lake Victoria Basin. The challenges included the need to understand the dynamics of water hyacinth infestation; its distribution, proliferation and impact modalities; and the development and implementation of appropriate weed control strategies and options. Most specific examples were taken from the Ugandan experience (NARO, 2002).

Lowering the excitation threshold of a random laser using the dynamic scattering states of an organosiloxane smectic A liquid crystal

Smectic A liquid crystals, based upon molecular structures that consist of combined siloxane and mesogenic moieties, exhibit strong multiple scattering of light with and without the presence of an electric field. This paper demonstrates that when one adds a laser dye to these compounds it is possible to observe random laser emission under optical excitation, and that the output can be varied depending upon the scattering state that is induced by the electric field. Results are presented to show that the excitation threshold of a dynamic scattering state, consisting of chaotic motion due to electro-hydrodynamic instabilities, exhibits lower lasing excitation thresholds than the scattering states that exist in the absence of an applied electric field. However, the lowest threshold is observed for a dynamic scattering state that does not have the largest scattering strength but which occurs when there is optimization of the combined light absorption and scattering properties. © 2012 American Institute of Physics.

Auto-calibration of a camera system using Image Alignment

Calibration of a camera system is a necessary step in any stereo metric process. It correlates all cameras to a common coordinate system by measuring the intrinsic and extrinsic parameters of each camera. Currently, manual calibration of a camera system is the only way to achieve calibration in civil engineering operations that require stereo metric processes (photogrammetry, videogrammetry, vision based asset tracking, etc). This type of calibration however is time-consuming and labor-intensive. Furthermore, in civil engineering operations, camera systems are exposed to open, busy sites. In these conditions, the position of presumably stationary cameras can easily be changed due to external factors such as wind, vibrations or due to an unintentional push/touch from personnel on site. In such cases manual calibration must be repeated. In order to address this issue, several self-calibration algorithms have been proposed. These algorithms use Projective Geometry, Absolute Conic and Kruppa Equations and variations of these to produce processes that achieve calibration. However, most of these methods do not consider all constraints of a camera system such as camera intrinsic constraints, scene constraints, camera motion or varying camera intrinsic properties. This paper presents a novel method that takes all constraints into consideration to auto-calibrate cameras using an image alignment algorithm originally meant for vision based tracking. In this method, image frames are taken from cameras. These frames are used to calculate the fundamental matrix that gives epipolar constraints. Intrinsic and extrinsic properties of cameras are acquired from this calculation. Test results are presented in this paper with recommendations for further improvement.

Comparison of manual and user guided methodologies for the classification and retrieval of construction site images

The amount of original imaging information produced yearly during the last decade has experienced a tremendous growth in all industries due to the technological breakthroughs in digital imaging and electronic storage capabilities. This trend is affecting the construction industry as well, where digital cameras and image databases are gradually replacing traditional photography. Owners demand complete site photograph logs and engineers store thousands of images for each project to use in a number of construction management tasks like monitoring an activity's progress and keeping evidence of the "as built" in case any disputes arise. So far, retrieval methodologies are done manually with the user being responsible for imaging classification according to specific rules that serve a limited number of construction management tasks. New methods that, with the guidance of the user, can automatically classify and retrieve construction site images are being developed and promise to remove the heavy burden of manually indexing images. In this paper, both the existing methods and a novel image retrieval method developed by the authors for the classification and retrieval of construction site images are described and compared. Specifically a number of examples are deployed in order to present their advantages and limitations. The results from this comparison demonstrates that the content based image retrieval method developed by the authors can reduce the overall time spent for the classification and retrieval of construction images while providing the user with the flexibility to retrieve images according different classification schemes.

Comparison of Civil Infrastructure Optical-based Spatial Data Acquisition Techniques

Infrastructure spatial data, such as the orientation and the location of in place structures and these structures' boundaries and areas, play a very important role for many civil infrastructure development and rehabilitation applications, such as defect detection, site planning, on-site safety assistance and others. In order to acquire these data, a number of modern optical-based spatial data acquisition techniques can be used. These techniques are based on stereo vision, optics, time of flight, etc., and have distinct characteristics, benefits and limitations. The main purpose of this paper is to compare these infrastructure optical-based spatial data acquisition techniques based on civil infrastructure application requirements. In order to achieve this goal, the benefits and limitations of these techniques were identified. Subsequently, these techniques were compared according to applications' requirements, such as spatial accuracy, the automation of acquisition, the portability of devices and others. With the help of this comparison, unique characteristics of these techniques were identified so that practitioners will be able to select an appropriate technique for their own applications.

Validation of Vision Tracking at Egnatia Odos Motorway

Tracking applications provide real time on-site information that can be used to detect travel path conflicts, calculate crew productivity and eliminate unnecessary processes at the site. This paper presents the validation of a novel vision based tracking methodology at the Egnatia Odos Motorway in Thessaloniki, Greece. Egnatia Odos is a motorway that connects Turkey with Italy through Greece. Its multiple open construction sites serves as an ideal multi-site test bed for validating construction site tracking methods. The vision based tracking methodology uses video cameras and computer algorithms to calculate the 3D position of project related entities (e.g. personnel, materials and equipment) in construction sites. The approach provides an unobtrusive, inexpensive way of effectively identifying and tracking the 3D location of entities. The process followed in this study starts by acquiring video data from multiple synchronous cameras at several large scale project sites of Egnatia Odos, such as tunnels, interchanges and bridges under construction. Subsequent steps include the evaluation of the collected data and finally, performing the 3D tracking operations on selected entities (heavy equipment and personnel). The accuracy and precision of the method's results is evaluated by comparing it with the actual 3D position of the object, thus assessing the 3D tracking method's effectiveness.

Automated Detection of Concrete Columns from Visual Data

After earthquakes, licensed inspectors use the established codes to assess the impact of damage on structural elements. It always takes them days to weeks. However, emergency responders (e.g. firefighters) must act within hours of a disaster event to enter damaged structures to save lives, and therefore cannot wait till an official assessment completes. This is a risk that firefighters have to take. Although Search and Rescue Organizations offer training seminars to familiarize firefighters with structural damage assessment, its effectiveness is hard to guarantee when firefighters perform life rescue and damage assessment operations together. Also, the training is not available to every firefighter. The authors therefore proposed a novel framework that can provide firefighters with a quick but crude assessment of damaged buildings through evaluating the visible damage on their critical structural elements (i.e. concrete columns in the study). This paper presents the first step of the framework. It aims to automate the detection of concrete columns from visual data. To achieve this, the typical shape of columns (long vertical lines) is recognized using edge detection and the Hough transform. The bounding rectangle for each pair of long vertical lines is then formed. When the resulting rectangle resembles a column and the material contained in the region of two long vertical lines is recognized as concrete, the region is marked as a concrete column surface. Real video/image data are used to test the method. The preliminary results indicate that concrete columns can be detected when they are not distant and have at least one surface visible.