New Eco-Friendly Coating Formulations to Improve Strength and Physical Properties of Recycled Paper Boards for Sustainable Packaging Applications

Ramnath Shenoy,Prakasha Shetty,Shivananda Wagle 한국펄프·종이공학회 2021 펄프.종이기술 Vol.53 No.3

Epigenetic regulation of vitamin D metabolism in human lung adenocarcinoma.

Ramnath, Nithya,Nadal, Ernest,Jeon, Chae Kyung,Sandoval, Juan,Colacino, Justin,Rozek, Laura S,Christensen, Paul J,Esteller, Manel,Beer, David G,Kim, So Hee Lippincott Williams Wilkins 2014 JOURNAL OF THORACIC ONCOLOGY Vol.9 No.4

<P>1α,25-Dihydroxyvitamin D3 (1,25-D3) is antiproliferative in preclinical models of lung cancer, but in tumor tissues, its efficacy may be limited by CYP24A1 expression. CYP24A1 is the rate limiting catabolic enzyme for 1,25-D3 and is overexpressed in human lung adenocarcinoma (AC) by unknown mechanisms.</P>

What is the Most Suitable Time Period to Assess the Time Trends in Cancer Incidence Rates to Make Valid Predictions - an Empirical Approach

Ramnath, Takiar,Shah, Varsha Premchandbhai,Krishnan, Sathish Kumar Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.8

Projections of cancer cases are particularly useful in developing countries to plan and prioritize both diagnostic and treatment facilities. In the prediction of cancer cases for the future period say after 5 years or after 10 years, it is imperative to use the knowledge of past time trends in incidence rates as well as in population at risk. In most of the recently published studies the duration for which the time trend was assessed was more than 10 years while in few studies the duration was between 5-7 years. This raises the question as to what is the optimum time period which should be used for assessment of time trends and projections. Thus, the present paper explores the suitability of different time periods to predict the future rates so that the valid projections of cancer burden can be done for India. The cancer incidence data of selected cancer sites of Bangalore, Bhopal, Chennai, Delhi and Mumbai PBCR for the period of 1991-2009 was utilized. The three time periods were selected namely 1991-2005; 1996-2005, 1999-2005 to assess the time trends and projections. For the five selected sites, each for males and females and for each registry, the time trend was assessed and the linear regression equation was obtained to give prediction for the years 2006, 2007, 2008 and 2009. These predictions were compared with actual incidence data. The time period giving the least error in prediction was adjudged as the best. The result of the current analysis suggested that for projections of cancer cases, the 10 years duration data are most appropriate as compared to 7 year or 15 year incidence data.

Micropropagation of Dendrobium fimbriatum Hook. By Green Pod Culture

Ramnath Sharma,K. K. De,Bibaychana Sharma,Sudipta Majumdar 한국식물학회 2005 Journal of Plant Biology Vol.48 No.2

Additive Properties of Crude, Age Specific and Age Adjusted Rates for Cancer Incidence and Mortality

Takiar, Ramnath,Shrivastava, Atul Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.13

Background: In National Cancer Registry Programme (NCRP) reports, various rates are routinely provided for 50 cancer sites of males and 54 cancer sites of females. Very often, depending on our interest, we wish to see these rates for group of cancers like head and neck cancers, oral cancers, and reproductive cancers. In such a situation, the desired rates are calculated independently from the actual data and reported. The question is can we derive the rates for groups of cancers from the published reports when the data is provided only for the individual sites? Objective: In the present paper, an attempt is made to explore the mathematical properties of various rates to derive them directly for the group of cancer sites from the published data when the rates are provided only for the individual sites. Source of data: The cancer incidence data collected by two urban Population Based Cancer Registries (PBCRs), under the network of NCRP for the period of 2006-08 was considered for the study purposes. The Registries included were: Bangalore and Bhopal. Results: In the present communication, we have shown that the crude rate (CR), age specific rates and age-adjuste rates (AAR) all possess additive properties. This means, given the above rates for individual sites, the above rates can be calculated for groups of sites by simply adding them. In terms of formula it can be stated that CR(Site1+Site2+++ SiteN) = CR(Site1)+CR(Site2) +++ CR(SiteN). This formula holds good for age specific rates as well as for AAR. This property facilitates the calculation of various rates for defined groups of cancers by simply adding the above rates for individual sites from which they are made up.

A Model Approach to Calculate Cancer Prevalence from 5 Years Survival Data for Selected Cancer Sites in India - Part II

Takiar, Ramnath,Krishnan, Sathish Kumar,Shah, Varsha Premchandbhai Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.14

Objective: Prevalence is a statistic of primary interest in public health. In the absence of good follow-up facilities, it is often difficult to assess the complete prevalence of cancer for a given registry area. An attempt is made to arrive at the complete prevalence including limited duration prevalence with respect of selected sites of cancer for India by fitting appropriate models to 1, 3 and 5 year cancer survival data available for selected registries of India. Methodology: Cancer survival data, available for the registries of Bhopal, Chennai, Karunagappally, and Mumbai was pooled to generate survival for the selected cancer sites. With the available data on survival for 1, 3 and 5 years, a model was fitted and the survival curve was extended beyond 5 years (up to 30 years) for each of the selected sites. This helped in generation of survival proportions by single year and thereby survival of cancer cases. With the help of estimated survived cases available year wise and the incidence, the prevalence figures were arrived for selected cancer sites and for selected periods. In our previous paper, we have dealt with the cancer sites of breast, cervix, ovary, lung, stomach and mouth (Takiar and Jayant, 2013). Results: The prevalence to incidence ratio (PI ratio) was calculated for 30 years duration for all the selected cancer sites using the model approach showing that from the knowledge of incidence and P/I ratio, the prevalence can be calculated. The validity of the approach was shown in our previous paper (Takiar and Jayant, 2013). The P/I ratios for the cancer sites of lip, tongue, oral cavity, hypopharynx, oesophagus, larynx, nhl, colon, prostate, lymphoid leukemia, myeloid leukemia were observed to be 10.26, 4.15, 5.89, 2.81, 1.87, 5.43, 5.48, 5.24, 4.61, 3.42 and 2.65, respectively. Conclusion: Cancer prevalence can be readily estimated with use of survival and incidence data.

A Model Approach to Calculate Cancer Prevalence From 5 Year Survival Data for Selected Cancer Sites in India

Takiar, Ramnath,Jayant, Kasturi Asian Pacific Journal of Cancer Prevention 2013 Asian Pacific journal of cancer prevention Vol.14 No.11

Background: Prevalence is a statistic of primary interest in public health. In the absence of good follow-up facilities, it is difficult to assess the complete prevalence of cancer for a given registry area. Objective: An attempt was here made to arrive at complete prevalence including limited duration prevalence with respect to selected sites of cancer for India by fitting appropriate models to 1, 3 and 5 years cancer survival data available for selected population-based registries. Materials and Methods: Survival data, available for the registries of Bhopal, Chennai, Karunagappally, and Mumbai was pooled to generate survival for breast, cervix, ovary, lung, stomach and mouth cancers. With the available data on survival for 1, 3 and 5 years, a model was fitted and the survival curve was extended beyond 5 years (up to 35 years) for each of the selected sites. This helped in generation of survival proportions by single year and thereby survival of cancer cases. With the help of survival proportions available year-wise and the incidence, prevalence figures were arrived for selected cancer sites and for selected periods. Results: The prevalence to incidence ratio (PI ratio) stabilized after a certain duration for all the cancer sites showing that from the knowledge of incidence, the prevalence can be calculated. The stabilized P/I ratios for the cancer sites of breast, cervix, ovary, stomach, lung, mouth and for life time was observed to be 4.90, 5.33, 2.75, 1.40, 1.37, 4.04 and 3.42 respectively. Conclusions: The validity of the model approach to calculate prevalence could be demonstrated with the help of survival data of Barshi registry for cervix cancer, available for the period 1988-2006.

Pattern of Reproductive Cancers in India

Takiar, Ramnath,Kumar, Sathish Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.2

Background: Reproductive cancers are those that affect the human organs that are involved in producing offspring. An attempt is made in the present communication to assess the magnitude and pattern of reproductive cancers, including their treatment modalities, in India. The cancer incidence data related to reproductive cancers collected by five population-based urban registries, namely Bangalore, Bhopal, Chennai, Delhi and Mumbai, for the years 2006-08 were utilized. The reproductive cancers among females constituted around 25% of the total and around 9% among males. Among females, the three major contributors were cervix (55.5%), ovary (26.1%) and corpus uteri (12.4%). Similarly among males, the three major contributors were prostate (77.6%), penis (11.6%) and testis (10.5%). For females, the AAR of reproductive cancers varied between 30.5 in the registry of Mumbai to 37.3 in the registry of Delhi. In males, it ranged between 6.5 in the registry of Bhopal to 14.7 in the registry of Delhi. For both males and females, the individual reproductive cancer sites showed increasing trends with age. The leading treatment provided was: radio-therapy in combination with chemo-therapy for cancers of cervix (48.3%) and vagina (43.9%); surgery in combination with chemo-therapy (54.9%) for ovarian cancer; and surgery in combination with radio-therapy for the cancers of the corpus uteri (39.8%). In males, the leading treatment provided was hormone-therapy for prostate cancer (39.6%), surgery for penile cancer (81.3%) and surgery in combination with chemo-therapy for cancer of the testis (57.6%).

인터워킹 프록시 기반 상업용 사물인터넷 제품 및 서비스 활용 방법

성낙명(Nak-Myoung Sung),체카람나스(Chekka Ramnath Teja),윤재석(Jaeseok Yun),최성찬(Sungchan Choi),안일엽(Il-Yeup Ahn),김재호(Jaeho Kim) 한국HCI학회 2016 한국HCI학회 학술대회 Vol.2016 No.1

Automated cross-sectional shape recovery of 3D branching structures from point cloud

Kresslein, Jacob,Haghighi, Payam,Park, Jaejong,Ramnath, Satchit,Sutradhar, Alok,Shah, Jami J. Society for Computational Design and Engineering 2018 Journal of computational design and engineering Vol.5 No.3

Many applications rely on scanned data, which can come from a variety of sources: optical scanners, coordinate measuring machines, or medical imaging. We assume that the data input to these applications is an unorganized point cloud or mesh of vertices. The objective may be to find particular features (medical diagnostics or reverse engineering) or comparison to some reference geometry (e.g. dimensional metrology). This paper focuses on the feature fitting of a segmented point cloud, specifically for branched, organic structures or structural frames, and targets non-monolithic geometries. In this paper, a methodology is presented for the automated recovery of cross-sectional shapes using centrally located curves. We assume a triangulated surface mesh is generated from the scanned point cloud. This surface mesh is the starting point for our methodology. We then find the curve skeleton of the part which abstractly describes the global geometry and topology. Next after segmenting the curve skeleton into non-branching segments, orthogonal planes to the curve skeleton segments, at preset or adaptive intervals, make slices through the surface mesh edges. The intersection points are extracted creating a 2D point cloud of the cross section. A number of application specific post-processing operations can be performed after obtaining the 2D point cloud cross sections and the curve skeleton paths including: calculations such as area or area moments of inertia, feature fitting or recognition, and digital shape reconstruction. Case studies are presented to demonstrate capabilities and limitations, and to provide insight into appropriate uses and adaptations for the presented methodology.