mCAT: Development of a Generic mHealth Tool for Continuous Assessment, Automatic Intervention, and Analysis

Use of mobile health (mHealth) technology for behavioral and psychological studies through continuous assessment and intervention is found to be effective. Also, the use of smartphone has increased rapidly last few years, as well as its uses for health support. mHealth research is applied for smoking cessation, motivating cancer survivors and mentoring peers for social engagement. While in most settings researchers are developing their own intervention and assessment tool for each different research. In this study mHealth research is applied and generalized across a range of applications, including smoking cessation, motivating cancer survivors and mentoring peers to improve social engagement. Here at Ubicomp Lab, Marquette University we have developed similar tool – Mobile peer-mentoring: An approach to making veterans seek mental health care support a normality, and Walking Forward for Physical Activity: The mHealth Tool for Motivating Cancer Survivors. This study analyzed these research, and proposed a design and implemented it as a generic mHealth tool, named mCAT (Mobile Continuous Assessment Tool). We also have shown the complexity to design challenges to develop an effective smartphone application that meets user expectation. The goal of this generic mHealth tool is to help future research designed for continuous assessment and intervention. This tool provides the initial building block as modules, customizable features, and API to start with the actual implementation. mCAT expects to be cost effective, easily customizable, leverage learning curve on the open standard

Evaluation of Rice Germplasm under Salt Stress at the Seedling Stage through SSR Markers

Twenty eight rice germplasms were used for identification of salt tolerant rice genotypes at the seedling stage at the experimental farm and Biotechnology laboratory of the Bangladesh Institute of Nuclear Agriculture (BINA), Mymensingh during February 2009 to October 2009. Phenotyping for salinity screening of the rice genotypes was done using salinized (EC level 12 dS m-1) nutrient solution in hydroponic system. Genotypes were evaluated for salinity tolerance on 1-9 scale based on seedling growth parameters following modified Standard Evaluation Scoring (SES) of IRRI. Phenotypically, on the basis of SES and % total dry matter (TDM) reduction of the genotypes viz. PBSAL-614, PBSAL-613, PBSAL-730, Horkuch, S-478/3 Pokkali and PBSAL (STL)-15 were found to be salt tolerant; on the other hand Iratom-24, S-653/32, S-612/32, S-604/32, S-633/32, Charnock (DA6), BINA Dhan-6 and S-608/32 were identified as salt susceptible. For genotyping, ten SSR markers were used for polymorphism, where 3 primers (RM127, RM443 and RM140) were selected for evaluation of salt tolerance. In respect of Primer RM127, 7 lines were found salt tolerant and 11 lines were moderately tolerant and 10 lines were susceptible. Nine tolerant, 9 moderately tolerant and 10 susceptible lines were found when the primer RM140 was used and primer RM443 identified 8 lines as tolerant, 9 lines as moderately tolerant and 11 lines as susceptible. Thus, the salt tolerant lines can be used in further evaluation for salinity tolerance and the SSR markers used in this study are proving valuable for identifying salt tolerant genes in marker assisted breeding. Int. J. Agril. Res. Innov. & Tech. 3 (1): 52-59, June, 2013 DOI: http://dx.doi.org/10.3329/ijarit.v3i1.1609

COMPARATIVE ADSORPTION STUDY ON RICE HUSK AND RICE HUSK ASH BY USING AMARANTHUS GANGETICUS PIGMENTS AS DYE

Low cost adsorbents such as Rice Husk (RH) and Rice Husk Ash (RHA) were used for removing dyes from aqueous medium and later Linear, Langmuir and Freundlich adsorption isotherms have been verified by using adsorption data. RH was activated by treating with nitric acid and RHA was prepared from RH by dolomite process. Natural dyes were extracted from the vegetable Amaranthus gangeticus by using a standard method. The removal efficiency of adsorbents was measured for the variation of parameters pH, contact time and adsorbents concentration. It has been noted that after changing time for same amount of adsorbent (1g/100ml) and dyes (10 ml) RH gave no efficiency trend but increased to 43.91% whereas for RHA efficiency was gradually increased to 59.62%. A reverse trend was noted when adsorption amounts were changed and others were put constant where RHA efficiency gradually increased to 99.30% but RH gave no trend with highest efficiency was close to 61.85%. The RH removal efficiency was good for pH 11 close to 62.86% and it was continuous from 3.95% at pH 2. Alternately, RHA gave 80.21% at pH 2 and later was decreased to 1.5% at pH 9 and again increased from pH 11. It is noted that RHA removal efficiency is better than RH and adsorptions are well fitted with isotherms

Occupational stress and addiction: Possible neurobiological elucidation of medical waste related individuals

Multiple factors contribute to the tendency to develop drug addictions, including social or psychological stressors. Most studies examining causes of and treatments for drug addiction have been conducted in Western developed nations. Here we used phenomenological research approach to explore the neurobiological explanation of drug addiction and to investigate attitudes towards drug use amongst individuals working with medical waste. Data were collected in Dhaka, the capital of Bangladesh, using a variety of techniques based on formal representative sampling for fixed populations and adaptive sampling for roaming populations. We found that over half of participants interviewed reported using illicit substances to cope with occupational stress. Self-reported disease symptoms related to stress were reported by most of the respondents. Working with horrifying waste contributes to increased stress among the participants. These results indicate that in the case of these workers, workplace stressors along with cultural and socio-economic context uniquely contribute to, and exacerbate, tendencies toward drug addiction

COMPARATIVE ADSORPTION STUDY ON RICE HUSK AND RICE HUSK ASH BY USING AMARANTHUS GANGETICUS PIGMENTS AS DYE

Low cost adsorbents such as Rice Husk (RH) and Rice Husk Ash (RHA) were used for removing dyes from aqueous medium and later Linear, Langmuir and Freundlich adsorption isotherms have been verified by using adsorption data. RH was activated by treating with nitric acid and RHA was prepared from RH by dolomite process. Natural dyes were extracted from the vegetable Amaranthus gangeticus by using a standard method. The removal efficiency of adsorbents was measured for the variation of parameters pH, contact time and adsorbents concentration. It has been noted that after changing time for same amount of adsorbent (1g/100ml) and dyes (10 ml) RH gave no efficiency trend but increased to 43.91% whereas for RHA efficiency was gradually increased to 59.62%. A reverse trend was noted when adsorption amounts were changed and others were put constant where RHA efficiency gradually increased to 99.30% but RH gave no trend with highest efficiency was close to 61.85%. The RH removal efficiency was good for pH 11 close to 62.86% and it was continuous from 3.95% at pH 2. Alternately, RHA gave 80.21% at pH 2 and later was decreased to 1.5% at pH 9 and again increased from pH 11. It is noted that RHA removal efficiency is better than RH and adsorptions are well fitted with isotherms

PARMA-CC: Parallel Multiphase Approximate Cluster Combining

Clustering is a common component in data analysis applications. Despite the extensive literature, the continuously increasing volumes of data produced by sensors (e.g. rates of several MB/s by 3D scanners such as LIDAR sensors), and the time-sensitivity of the applications leveraging the clustering outcomes (e.g. detecting critical situations, that are known to be accuracy-dependent), demand for novel approaches that respond faster while coping with large data sets. The latter is the challenge we address in this paper. We propose an algorithm, PARMA-CC, that complements existing density-based and distance-based clustering methods. PARMA-CC is based on approximate, data parallel cluster combining, where parallel threads can compute summaries of clusters of data (sub)sets and, through combining, together construct a comprehensive summary of the sets of clusters. By approximating clusters with their respective geometrical summaries, our technique scales well with increased data volumes, and, by computing and efficiently combining the summaries in parallel, it enables latency improvements. PARMA-CC combines the summaries using special data structures that enable parallelism through in-place data processing. As we show in our analysis and evaluation, PARMA-CC can complement and outperform well-established methods, with significantly better scalability, while still providing highly accurate results in a variety of data sets, even with skewed data distributions, which cause the traditional approaches to exhibit their worst-case behaviour. In the paper we also describe how PARMA-CC can facilitate time-critical applications through appropriate use of the summaries