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ALLIANCE BETWEEN BARN SWALLOW HIRUNDO RUSTICA LINNAEUS, 1758 AND INDIAN MUSTARD BRASSICA JUNCEA (L.) CZERNAJEW, 1859: A NEW INTUITION IN BIRD-PLANT ECOLOGICAL NETWORKS
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The habitat type and food availability always influence the population size of many
organisms. Bird’s feeding pattern should be abstracted to complete avian community structure
data. The agronomy main research farm of Orissa University of Agriculture and Technology
is a well-managed multi-crop agro-ecosystem which provides a suitable ground for ecological
research. In a multi-crop farmland, the association of Barn Swallow Hirundo rustica Linnaeus,
1758, with the Indian mustard Brassica juncea (L.) Czernajew, 1859 crops have been
recorded for the first time while hovering only on this field. A flock of Barn swallows was
recorded in 32 field visits while flying continuously over the Indian mustard field after
flowering to ripening of fruit in the morning and sometimes in afternoon also. The range of
the birds was recorded from 6 to 61 with a mean individual of 36.03 ± 15.37 hovering for
1.83 hr daily. This may be the behaviour for the feeding pattern of these flying insectivorous
birds which was not seen in other crop-fields with same insect diversity describing it as not
the only reason for this behaviour. To reveal this poorly understood behaviour of flying
insectivore birds, a detailed long term behavioural study with gut content analysis is needed to
explain the particular reason behind this behaviour of Barn swallows which will support the
conservation of these birds and control their population decline.

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Publication Date
Mon Sep 04 2017
Journal Name
Journal Of Chemical And Pharmaceutical Research
Lead, Cadmium and Nickel contamination of roadside soils and plant leaves in Baghdad City
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Publication Date
Fri Dec 01 2023
Journal Name
Kufa Journal For Agricultural Sciences
The effect of some food sources and hive products on the oriental hornet Vespa orientalis Linnaeus 1771 (Hymenoptera: Vespidae)
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This study was carried out in the bee laboratory in the Faculty of Agriculture –University of Kufa in September 2021 to evaluate some protein sources and hive products against the oriental hornet Vespa orientalis Linnaeus 1771 (Hymenoptera: Vespidae). The food sources included: beef meat, gut fish, beef lung, honeybee, wax, propolis, pollen, bee worker, and water, in addition to control which was an empty petri dish. The number of visits and their duration were calculated. The results showed that the wasps preferred bee honey and wax significantly higher than the rest of the stimuli.

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering
Developing a Model to Estimate the Productivity of Ready Mixed Concrete Batch Plant
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Productivity estimating of ready mixed concrete batch plant is an essential tool for the successful completion of the construction process. It is defined as the output of the system per unit of time. Usually, the actual productivity values of construction equipment in the site are not consistent with the nominal ones. Therefore, it is necessary to make a comprehensive evaluation of the nominal productivity of equipment concerning the effected factors and then re-evaluate them according to the actual values.

In this paper, the forecasting system was employed is an Artificial Intelligence technique (AI). It is represented by Artificial Neural Network (ANN) to establish the predicted model to estimate wet ready mixe

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Thu Aug 01 2019
Journal Name
Ieee Internet Of Things Journal
A New Task Allocation Protocol for Extending Stability and Operational Periods in Internet of Things
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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

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Publication Date
Sun Nov 26 2017
Journal Name
Journal Of Engineering
Compression Index and Compression Ratio Prediction by Artificial Neural Networks
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Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Molecular Structure
A new thiazoldinone and triazole derivatives: Synthesis, characterization and liquid crystalline properties
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Publication Date
Thu Nov 15 2018
Journal Name
Journal Of Mathematical Imaging And Vision
A New Hybrid form of Krawtchouk and Tchebichef Polynomials: Design and Application
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Agricultural And Statistical Sciences
A COMPARISON BETWEEN SOME HIERARCHICAL CLUSTERING TECHNIQUES
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In this paper, some commonly used hierarchical cluster techniques have been compared. A comparison was made between the agglomerative hierarchical clustering technique and the k-means technique, which includes the k-mean technique, the variant K-means technique, and the bisecting K-means, although the hierarchical cluster technique is considered to be one of the best clustering methods. It has a limited usage due to the time complexity. The results, which are calculated based on the analysis of the characteristics of the cluster algorithms and the nature of the data, showed that the bisecting K-means technique is the best compared to the rest of the other methods used.

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Publication Date
Sun Jun 06 2010
Journal Name
Baghdad Science Journal
Effect of Hardening to drought Tolerance on the Moisture Content of Sunflower Plant. III. Moisture Percentage in Whole Plant
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The study was conducted during spring seasons of 2000 and 2001.The aim was to study the changes in the moisture content of sunflower plants during growth stages under hardening conditions to drought tolerance .Agricultural practices were made according to recommendation. Asplit-split plots design was used with three replications. The main plots included irrigation treatments:irrigation to100%(full irrigation),75and50%of available water. The sub plots were the cultivars Euroflor and Flame.The sub-sub plots represented four seed soaking treatments: Control (unsoaked), soaking in water ,Paclobutrazol solution(250ppm),and Pix solution(500ppm). The soaking continued for 24 hours then seeds were dried at room temperature until they regained t

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