A Study of Correlation Analysis between Feces Activity Area and Environment Factors against Western Honeybee (Apis mellifera)

2021 ◽  
Vol 36 (3) ◽  
pp. 77-87
Author(s):  
Bo-Sun Park ◽  
Yong-Soo Choi ◽  
Eun-Jin Kang ◽  
Heegeun Park ◽  
Olga Frunze ◽  
...  
Keyword(s):  
Apis Mellifera ◽  
Correlation Analysis ◽  
Environment Factors ◽  
Activity Area

scholarly journals Response of Colony Strength to Honey Production: Regression and Correlation Analysis

2006 ◽  
Vol 27 ◽  
pp. 133-137 ◽  
Author(s):  
SJ Bhusal ◽  
RB Thapa
Keyword(s):  
Apis Mellifera ◽  
Correlation Analysis ◽  
Foraging Activity ◽  
Brood Rearing ◽  
Honey Production ◽  
Exponential Increase ◽  
Flowering Season ◽  
Positive Linear Correlation ◽  
Comb Building ◽  
Four Levels

An experiment was conducted using Randomized Complete Block (RCB) design to find the effects of initial colony strength of Apis mellifera L. on honey production with four levels of initial populations: 4 frames (9,800), 6 frames (14,700), 8 frames (19,600) and 10 frames (24,500) of adult honeybees per colony replicating 5 times during litchi flowering season (February to April, 2003) in Chitwan. This study revealed the exponential increase in honey production {Y = 4.22 – 0.7325 X + 0.09625 X2 (4 ≤X ≤ 10 comb covered by bees per colony) and Y = 4.22 – 0.000299 X + 0.000000016 X2 (9,800 ≤ X ≤ 24,500 honeybees per colony), n = 4} producing 2.32, 1.59 and 1.18 times more honey from initially 10-, 8- and 6-frame colonies as compared to the honey production of 2.82 kg/colony from 4-frame colonies. There was significantly positive linear correlation among colony attributes like colony strength, brood rearing, comb building, foraging activity and honey production. Key words: Apis mellifera, honey bee population, colony attributes J. Inst. Agric. Anim. Sci. 27:133-137 (2006)

Microdensitometer—computer correlation analysis of ultrastructural periodicity

1978 ◽  
Vol 36 (2) ◽  
pp. 32-33
Author(s):  
D.R. Ensor ◽  
C.G. Jensen ◽  
J.A. Fillery ◽  
R.J.K. Baker
Keyword(s):  
Correlation Analysis ◽  
Background Noise ◽  
Computer Control ◽  
Optical Diffraction ◽  
Screw Thread ◽  
Straight Line ◽  
Computer Storage ◽  
Correlation Process ◽  
Electron Microscope Image ◽  
Fixed Beam

Because periodicity is a major indicator of structural organisation numerous methods have been devised to demonstrate periodicity masked by background “noise” in the electron microscope image (e.g. photographic image reinforcement, Markham et al, 1964; optical diffraction techniques, Horne, 1977; McIntosh,1974). Computer correlation analysis of a densitometer tracing provides another means of minimising "noise". The correlation process uncovers periodic information by cancelling random elements. The technique is easily executed, the results are readily interpreted and the computer removes tedium, lends accuracy and assists in impartiality.A scanning densitometer was adapted to allow computer control of the scan and to give direct computer storage of the data. A photographic transparency of the image to be scanned is mounted on a stage coupled directly to an accurate screw thread driven by a stepping motor. The stage is moved so that the fixed beam of the densitometer (which is directed normal to the transparency) traces a straight line along the structure of interest in the image.

Differentiation Processes of the Ocellar Retina of the Honeybee (Apis Mellifera L.)

1990 ◽  
Vol 48 (3) ◽  
pp. 430-431
Author(s):  
Maria Anna Pabst
Keyword(s):  
Apis Mellifera ◽  
Distal Part ◽  
Cell Layer ◽  
Single Layer ◽  
Photoreceptor Cells ◽  
Distal Segment ◽  
Compound Eyes ◽  
Thin Sections ◽  
Ultrastructural Studies ◽  
Adult Worker

In addition to the compound eyes, honeybees have three dorsal ocelli on the vertex of the head. Each ocellus has about 800 elongated photoreceptor cells. They are paired and the distal segment of each pair bears densely packed microvilli forming together a platelike fused rhabdom. Beneath a common cuticular lens a single layer of corneagenous cells is present.Ultrastructural studies were made of the retina of praepupae, different pupal stages and adult worker bees by thin sections and freeze-etch preparations. In praepupae the ocellar anlage consists of a conical group of epidermal cells that differentiate to photoreceptor cells, glial cells and corneagenous cells. Some photoreceptor cells are already paired and show disarrayed microvilli with circularly ordered filaments inside. In ocelli of 2-day-old pupae, when a retinogenous and a lentinogenous cell layer can be clearly distinguished, cell membranes of the distal part of two photoreceptor cells begin to interdigitate with each other and so start to form the definitive microvilli. At the beginning the microvilli often occupy the whole width of the developing rhabdom (Fig. 1).

The German Strengths and Difficulties Questionnaire (SDQ)

2010 ◽  
Vol 26 (4) ◽  
pp. 256-262 ◽  
Author(s):  
Ulrike Petermann ◽  
Franz Petermann ◽  
Ina Schreyer
Keyword(s):  
Correlation Analysis ◽  
Teacher Ratings ◽  
Screening Instrument ◽  
Preschool Age ◽  
Strengths And Difficulties Questionnaire ◽  
Preschool Age Children ◽  
Discriminant Analyses ◽  
Strengths And Difficulties ◽  
Behavioral Attributes ◽  
And Behavior

The Strengths and Difficulties Questionnaire (SDQ) is a screening instrument that addresses positive and negative behavioral attributes of children and adolescents. Although this questionnaire has been used in Germany to gather information from parents and teachers of preschoolers, few studies exist that verify the validity of the German SDQ for this age. In the present study, teacher ratings were collected for 282 children aged 36 to 60 months (boys = 156; girls = 126). Likewise, teacher ratings were collected with another German checklist for behavior problems and behavior disorders at preschool age (Verhaltensbeurteilungsbogen für Vorschulkinder, VBV 3–6). Moreover, children’s developmental status was assessed. Evaluation included correlation analysis as well as canonical correlation analysis to assess the multivariate relationship between the set of SDQ variables and the set of VBV variables. Discriminant analyses were used to clarify which SDQ variables are useful to differentiate between children with or without developmental delay in a multivariate model. The results of correlation and discriminant analyses underline the validity of the SDQ for preschoolers. According to these results, the German teacher SDQ is recommended as a convenient and valid screening instrument to assess positive and negative behavior of preschool age children.

Analysis of Maximum Expiratory Flow Volume Curves Using Canonical Correlation Analysis

1985 ◽  
Vol 24 (02) ◽  
pp. 91-100 ◽  
Author(s):  
W. van Pelt ◽  
Ph. H. Quanjer ◽  
M. E. Wise ◽  
E. van der Burg ◽  
R. van der Lende
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Flow Volume ◽  
Non Linear ◽  
Maximum Expiratory Flow ◽  
Expiratory Flow ◽  
Relationship Of ◽  
The Relationship ◽  
Age And Sex

SummaryAs part of a population study on chronic lung disease in the Netherlands, an investigation is made of the relationship of both age and sex with indices describing the maximum expiratory flow-volume (MEFV) curve. To determine the relationship, non-linear canonical correlation was used as realized in the computer program CANALS, a combination of ordinary canonical correlation analysis (CCA) and non-linear transformations of the variables. This method enhances the generality of the relationship to be found and has the advantage of showing the relative importance of categories or ranges within a variable with respect to that relationship. The above is exemplified by describing the relationship of age and sex with variables concerning respiratory symptoms and smoking habits. The analysis of age and sex with MEFV curve indices shows that non-linear canonical correlation analysis is an efficient tool in analysing size and shape of the MEFV curve and can be used to derive parameters concerning the whole curve.

Detection of the Structural Failing Point Using Correlation and Local Correlation Analysis

2020 ◽  
Author(s):  
Hyounkyun Oh ◽  
Younghan Jung ◽  
Junyong Ahn ◽  
Sujin Kim ◽  
M. Myung Jeong
Keyword(s):  
Correlation Analysis ◽  
Local Correlation
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