A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Manjula, A.
- Site Distribution of Different Types of Cutaneous Malignancy
Authors
1 Department of Pathology, S. S. Institute of Medical Sciences & Research Centre, "Jnanashankara". NH - 4, Bypass road, Davangere - 577 005, Karnataka, IN
2 Department of Pathology, S.S. Institute of Medical Sciences and Research Center, Davangere, IN
Source
Indian Journal of Public Health Research & Development, Vol 3, No 3 (2012), Pagination: 76-79Abstract
Background: Dermatological malignancies are relatively uncommon. Since the investigation, at an individual level, of various aspects of lifetime sun exposure, however, remains difficult, comparison of the site distribution and age pattern of different types of skin cancer can be an important source of aetiological clues. This study sought to evaluate the site distribution and age pattern of three main types of skin cancer in our setting.
Methods: The present study is a descriptive analysis of three main skin cancers seen in a tertiary hospital in Davangere. Histologically diagnosed various skin cancers i.e. malignant melanoma (MM), basal-cell carcinoma (BCC) and squamous-cell carcinoma (SCC) from January 2005 to December 2009 were reviewed and analyzed according to age, gender and site of distribution.
Results: During the study period forty tissue samples received were histologically confirmed to be of common primary skin cancers. The ages of the patients ranged from 18 and 80 years (mean: 51.4years). Squamous cell carcinoma (SCC) was the most common malignancy consisting of 26 (65 %) cases followed by melanoma with 9 (22.5%) cases and basal cell carcinoma (BCC) with 5 (12.5%) cases. The most common incidence was among the age group 40-60 years with 20(50%) cases detected. The head and neck was the commonest site of involvement for SCC and BCC, whereas for melanoma it was lower extremities.
Conclusion: Squamous cell carcinoma, Basal cell carcinoma and malignant melanoma constitute three main histotypes of skin cancer. SCC and BCC compared to malignant melanoma affect body locations which are usually sun exposed. Age-related behavior (i.e., another indirect indicator of duration of exposure to UV light) is consistent with the anatomical distribution of skin cancer.
Keywords
Squamous Cell Carcinoma, Basal Cell Carcinoma, Malignant Melanoma, Site Distribution
References
- Franceschi S, Levi F, Randimbison L, Vecchia CL. Site distribution of different types of skin cancer: new aetiological clues. Int J Cancer 1996; 67:24-28.
- Krickera, Armstronbg K, Englishd R, Heenanp J. Adose-response curve for sun exposure and basal-cell carcinoma. Int J Cancer 1995; 60:482- 488.
- Armstrong K. Epidemiology of malignant melanoma: intermittent or total accumulated exposure to the sun? J dermatol Surg Oncol 1988; 14:835-849.
- Levi F, Franceschi S, Randimbison L, Vecchia CL. Trends of skin cancer in the Canton of Vaud, 1976-92. Br J Cancer 1995; 72:1047-1053.
- Moan J, Dahlback A. The relationship between skin cancers, solar radiation and ozone depletion. Br J Cancer 1992; 65:916-921.
- Osterlind A, Jensen KH, Jensen OM. Incidence of cutaneous malignant melanoma in Denmark 1978-1982. Anatomic site distribution, histologic types, and comparison with non-melanoma skin cancer. Br J Cancer 1988; 58:385-391.
- Kaldorj, Shuggd, Youngb, Dwyert, WANG YG. Non-melanoma skin cancer: ten-year experience of cancer-registry based surveillance. Int J Cancer 1993; 53:886-891.
- Asuquo ME, Otei O, Umana A, Bassey I, Ebughe G. Skin malignancy of the head and neck in Calabar, Southern Nigeria. European J plastic surgery 2010; 33:87-89
- Laishram RS, Banerjee A, Punyabati P, Sharma DC. Pattern of skin malignancies in Manipur, India: A 5-year histopathological review. J Pakistan Association of Dermol 2010; 20: 128-132.
- Crombie ki. Distribution of malignant melanoma on the body surface. Br. J. Cancer 1981; 43:842
- Cutanee T, Calaber, Sud Nd. Skin malignancies in Calabar, Southern Nigeria. J. Afr. Cancer 2009; 1:159-163
- Deo SV, Sidhartha H, Shukla NK et al. Surgical management of skin cancers: experience from a regional cancer centre in North India. Ind J Cancer 2005; 42:145-150.
- Ochicha O, Edino ST, Mohamed AZ, Umar AB: Dermatological malignancies in Kano, Nigeria: a histopathological review. Annal African Med 2004; 3:188-191.
- Al-Thobhani AK, Raja YA, Norman TA.The pattern and distribution of malignant neoplasms among Yemeni patients. Saudi Med J 2001; 22: 910-913.
- Alakloby OM, Bukhari IA, Shawarby MA. Histopathological pattern of non melanoma skin cancers at King Fahd Hospital of the University in the Eastern Region of Saudi Arabia during the years1983-2002. Cancer Ther 2008; 6:303-306.
- Al-Maghrabi JA, Al-Ghamdi AS, Elhakeem HA. Pattern of skin cancer in south western Saudi Arabia. Saudi Med J 2004; 25: 776-779.
- Microbial Diversity in Termite Nest
Authors
1 Department of Genetics, School of Biological Sciences, Madurai Kamaraj University, Madurai 625 021, IN
Source
Current Science, Vol 106, No 10 (2014), Pagination: 1430-1434Abstract
In the present study, the microbial diversity of termite nest was studied using bacterial tag encoded amplicon pyrosequencing by both culture-dependent and culture-independent approaches. A total of 10,793 and 4,777 high-quality reads were obtained in cultureindependent and culture-dependent approaches respectively. The former approach revealed dominant phyla Proteobacteria (32%) and Actinobacteria (20%), whereas the latter approach revealed Firmicutes (74%) and Proteobacteria (22%) as the most dominant phyla. The significant variation in the microbial diversity and composition of termitarium assessed by the two approaches could be due to the fact that culture-dependent approach explored only selected groups of microbial population, whereas metagenomic approach explored complete microbial diversity of termitarium, which provides credence to the application of metagenomic strategy to explore novel microbial species.Keywords
Metagenome, Microbial Diversity, Pyrosequencing, Termitarium.Full Text
- Distance Based Query Processing in Mobile Applications
Authors
1 Department of Information & Communication Engineering, Anna University, Chennai, IN
Source
Networking and Communication Engineering, Vol 6, No 2 (2014), Pagination:Abstract
A digital ecosystem which have been motivated by natural systems aspire to deliver the complication of digital world which is likely to have the properties to self- organize , is scalable and is achievable . Distributed wireless mobile network is the main technology in a digital ecosystem. It provides information exchange and information services that are to be delieverd , which satisfies the requirement for digital ecosystems. Many drivers utilize Global Positioning System (GPS) to replace traditional printed map with ongoing development of the motor industry and mobile communication technology. Given a group of candidate interest objects, a question purpose, and therefore the variety of objects k, dkNN finds the shortest path that goes through all k interest objects with the minimum shortest distance among all attainable methods. By following this path, the user can visit all k interest objects one by one. This path has the shortest distance among all other possible paths. The algorithm functions well if the density is high and the number of interest objects is smaller than seven. This method works on both small and large number of nodes. And also increases the result accuracy for small and large number of nodes.Keywords
Digital EcoSystem, Query Processing.- Detection of Green and Orange Colour Fruits in Outdoor Condition Using Robotic Applications
Authors
1 Department of ICE, Tamilnadu College of Engineering, IN
2 Department of ICE, Tamilnadu College of Engineering, IN
Source
Fuzzy Systems, Vol 9, No 6 (2017), Pagination: 109-113Abstract
This project is developed for an automation purpose which is suitable for juice making industries. For this, we will be using image processing for detecting the colour. By using image sensor, we will be monitoring the fruits which are moving in a conveyor belt. The monitored information will be sent to image processing section. By using LABVIEW we will be processing the images and as the result we will get an extracted colour of the input product. If the fruits are yellowish green, then it will be processed to the next section and if the fruits are not in expected colour, then we will get an alert saying that the corresponding fruit is not suitable for the next process. By using RTC, we will be monitoring the shift timings and based on the shift timings, production output will be calculated.References
- A. R. JIMENZE, R. CERES, J.L. Pons, ”A Survey of computer vision method for locating fruits on trees”Trans.ASAE,vol.43, no.6,2000, pp.1911-1920.
- D.M.BULANON, T.K KATAOKA, S. ZHANG, T.OTA, T.HIROMA “Optional Thresholding for the Automatic Recognition of Apple Fruits,” ASAE 2001, NO 01-3133.
- Automation in Biogas Plant using PLC, SCADA, GSM
Authors
1 Department of Instrumentation and Control Engineering, Tamilnadu College of Engineering., IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 9, No 6 (2017), Pagination: 120-126Abstract
Biomethanation is a process of generating biogas from organic waste such as food waste, industrial waste, night soil waste, cow dung among other organic wastes. Small and medium size conventional biogas plants are operated manually and this method has many challenges. The health of the digester/fermentation tank has to be monitored on a regular basis for stable biogas generation process. Biogas plant has four major processes starting from organic waste collection and mixing, digestion, gas collection and gas distribution. In order to operate the biogas plant at an optimal level without any stoppages implementation of Automation will be important to mitigate the challenges faced in conventional biogas plant. .In this system the overall process are controlled by programmable logic controller and field instruments. And also these processes are controlled by PLC and monitored by SCADA using software. The project uses fabric digesters instead of the typical mild steel or concrete based digesters and the idea to control the plant using GSM module is also being suggested. The obtained biogas is used for as fuel in cooking and also for generation of electricity.Keywords
PLC, SCADA, GSM, Biomethanation, Biogas.References
- E. V. Prakash, L. P. Singh, “Biomethanation of vegetable and fruit waste in co-digestion”, International Journal of Emerging Technology and Advanced Engineering, Certified Journal, vol. 3, no. 6, (2013).
- S. Chelliapan, S. B.Mahat, “Anaerobic Digestion of Paper Mill Wastewater”, Iranica Journal of Energy & Environment 3 (Special Issue on Environmental Technology):pp.85-90, ISSN 2079-2115, (2012).
- https://en.wikipedia.org/wiki/Anaerobic_digestion.
- R.S. Khoiyangbam, “Environmental Implications of Biomethanation in Conventional Biogas Plants”, Iranica Journal of Energy & Environment 2 (2): pp.181-187, ISSN 2079-2115, (2011).
- A.N. Sarkar, “Research and development work in biogas Technology”, Journal of Scientific and Industrial Res., vol. 41, (2014), pp.279-291
- B. Demirel, P. Scherer, “The roles of acetotrophic and hydrogenotrophic methanogens during anaerobic conversion of biomass to methane: a review”, Rev. Environ. Sci. Biotechnol. vol.7, (2008), pp.173-190
- https://en.wikibooks.org/wiki/Introductory_PLC_Programming.
- Rexroth indralogic L20 03VRS system description – operating and programming guide, (2004).
- D. Baily, E. Wright, “Practical SCADA for Industry”, Elsevier journal of Process Plant, May (2003)
- Assessment of Risk Factors for Diabetes among Bank Employees Using Indian Diabetes Risk Score: A Cross Sectional Study
Authors
1 PG Tutor, Community Medicine , AJIMS & RC, IN
2 Assistant Professor, Community Medicine AJIMS & RC, IN
3 Assistant Professor, Community Medicine, AJIMS & RC, IN
4 Professor, Community Medicine, AJIMS & RC., IN
5 HOD, Professor, Community Medicine, AJIMS & RC, IN
Source
Indian Journal of Public Health Research & Development, Vol 11, No 1 (2020), Pagination: 609-615Abstract
Introduction: Diabetes is an “iceberg” disease and is one of the major causes of premature illness and death worldwide. From 108 million in 1980, the number of people living with diabetes has increased to 422 million in 2014. In india it was the 7th biggest cause for early death in 2016. There are many screening tools available to identify the risk for diabetes, of which IDRS tool is one of them.
Objective: To assess risk of diabetes mellitus among selected bank employees using Indian diabetes risk score.
Methodology: A cross sectional study was conducted over a period of 2 months (February to march 2019) among 205 employees of 4 branches of a selected bank. Data was collected by purposive sampling using a pre-tested, semi-structured questionnaire and IDRS scale. Clinical examination and GRBS was carried out. Chi-square test was used as test for association.
Results: Among 205 respondents, IDRS score showed that 61% belonged to high risk category, 25% to moderate risk & 14% belonged to low risk.
Conclusion: Present study showed 61% to be in high risk category for DM; it also revealed significant association between overweight and high IDRS. Age, abdominal obesity in males, family history of diabetes and physical activity were significantly associated with high IDRS. Early screening aids in early diagnosis and treatment which can reduce the burden of DM.