scholarly journals Age-estimation of the Christmas Tree Worm Spirobranchus giganteus (Pomlychaeta, Serpulidae) Living Buried in the Coral Skeleton from the Coral-growth Band of the Host Coral

1996 ◽  
Vol 62 (3) ◽  
pp. 400-403 ◽  
Author(s):  
Eijiroh Nishi ◽  
Moritaka Nishihira
2019 ◽  
Vol 11 (2) ◽  
pp. 264-271
Author(s):  
Oktiyas Muzaky Luthfi ◽  
Sigit Rijatmoko ◽  
Andik Isdianto ◽  
Daduk Setyohadi ◽  
Alfan Jauhari ◽  
...  

Coral reef is a massive natural building block that mainly composed of hard coral. In ecological view coral reef is the center of biological activity for shelter, foraging and feeding place. Porites lutea is a common coral in reef flat area such as in Pantai Kondang Merak. This coral can form a massive with hillocky colony surface and has a slow linear extension rate, that made this coral has long longevity. The annual growth band of coral skeleton provide information of pollutants in the coastal extending back over several years ago due to ability of coral aragonite traped trace metal from environment. The aim of this research was to determine the concentration of trace metals of Cd, Cu and As along with the coral annual banding. The heavy metals detection was performed using ICP-OES (iCAP 7400 Series). The concentration of Cd, Cu and As in sample 1 (KM1) were 2.236 mg/kg, 9.726 mg/kg, and 2.474 mg/kg, while sample 2 (KM2) were 1.989 mg/kg, 19.157 mg/kg, and 2,064 mg/kg respectively. Two ways mechanism of trace metals to be trapped in the coral skeleton are by direct mechanism when trace metals in a form dissolved ion that were uptaken by coral then stored into coral skeleton and by indirect mechanism when particulate metals ingested by plankton then eaten by coral through coral tissue. The tracing of heavy metal in coral is provided important information of environment condition of the sea from 2009 - 2015 that may be used for authority decision regarding pollutant ambient in the sea environment.


2021 ◽  
Vol 8 ◽  
Author(s):  
Kyle W. Fouke ◽  
Jeffrey M. Trop ◽  
Mayandi Sivaguru

Next-generation high resolution brightfield microscopy, x-radiography, and microcomputed tomography (microCT) analyses indicate that coral skeleton high density band (HDB) and low density band (LDB) stratigraphic sequences record dynamic changes in coral growth history. HDB-LDB sequences were studied within three small heads of Orbicella annularis, an ecological keystone species in the Caribbean Sea, collected from the leeward fringing reefs on Curaçao. Results indicate that HDB layers are formed by the thickening of exothecal and endothecal dissepiments, costae, and theca located at the margin and external to individual skeletal cups (corallites). Conversely, septa and columellas located inside individual corallites do not change in thickness. HDB-LDB stratigraphic sequences were laterally traced from the center to the margins of individual coral heads, demonstrating that shifts took place in the trajectory of coral skeleton growth. Normal HDB layers in the center of individual coral heads are formed at the same time (age-equivalent) as surfaces of erosion and no skeleton growth (hiatuses) on the margins of the heads. These hiatus surfaces within HDB-LDB stratal geometries indicate that multiple marine ecological and environmental processes affect the orientation, size, shape, and geometry of coral skeletons during coral growth history. The presence of these hiatus surfaces in other large coral heads would strongly impact sclerochronology and the interpretation of multiple environmental factors including sea surface temperature (SST).


JKCD ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 9-11
Author(s):  
Sadaf Ambreen

Objectives: To compare Demirjian Dental scoring method with Greulich-Pyle (GP) Skeletal method of age estimation in pubertal children. Materials and Methods: Sample of the study included 267 male healthy subjects of 11-16 years of age group.. Demirjian Scoring system was utilized to evaluate the orthopantomograms to assess their Dental age and the Hand-Wrist radiographs were analyzed to calculate the skeletal age by utilizing GP atlas. Chronological age was obtained from the date of birth of the subject .Both methods were compared with one another and with the chronological age. It was a cross-sectional study and only healthy male subjects without any clinical abnormalities were included in the study. Results: A total of 267 male subjects of 11-16 years of age group were assessed by Demirjian and Greulich Pyle Methods. Both were compared with Chronological Age. Data obtained was statistically analyzed and the Student “t” test was applied in the study population. The mean difference between Chronolgical age and dental age was 0.69years and that of chronological age and skeletal age was 0.87 years. It was observed from dental age assessment that it does not differ much from the skeletal age. Conclusion: It was concluded that Demirjian method of Age Estimation is more precise than Greulich Pyle method of Age Estimation. Furthermore both methods can be used selectively in Medicolegal cases to access bone age which can be easily correlated to chronological age.


2018 ◽  
Vol 4 (10) ◽  
pp. 6
Author(s):  
Khemchandra Patel ◽  
Dr. Kamlesh Namdev

Age changes cause major variations in the appearance of human faces. Due to many lifestyle factors, it is difficult to precisely predict how individuals may look with advancing years or how they looked with "retreating" years. This paper is a review of age variation methods and techniques, which is useful to capture wanted fugitives, finding missing children, updating employee databases, enhance powerful visual effect in film, television, gaming field. Currently there are many different methods available for age variation. Each has their own advantages and purpose. Because of its real life applications, researchers have shown great interest in automatic facial age estimation. In this paper, different age variation methods with their prospects are reviewed. This paper highlights latest methodologies and feature extraction methods used by researchers to estimate age. Different types of classifiers used in this domain have also been discussed.


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