Chennai Dost - LGBT Peer Counseling Report (April 2013 - March 2014)

"Peer counseling in one way this community can be reached and helped. Through this year’s report we are able to understand that physiologically and psychologically the community is extremely vulnerable and at risk. They go through immense stress and depression which affects them emotionally and mentally forcing them to be suicidal, abuse substance and practice unsafe sex. Most targeted interventions and counseling is offered to MSM (Men who have sex with men) below the poverty line, but the majority of LGBT are from the middle and the lower middle class who are oblivious of any such services, they should be at least a platform or a forum for them to be educated about sex, sexuality, their rights and offer support. Chennai Dost is a self funded group trying its best to reach out to this invisible community hoping to help and make a visible difference when there is enough resource.

Climate change vulnerability assessment among rainfed smallholder farmers: a case analysis from Indian watersheds

Climate change and its unavoidable impacts are being felt around the world which is why vulnerability assessments are essential planning tools for defining the climate change associated risks, for generating better policies as well as for identifying location specific adaptation strategies. Tropical rainfed agriculture is of specific interest as it holds the majority of world food production, dominated by smallholder farming which are notably vulnerable to climate change. However, only few studies have been conducted on the vulnerability of smallholders in the rainfed tropics, especially in India, a country that will be particularly affected by climate change. This study focuses on climate vulnerability assessment among smallholder farms in three Watershed Development Programme (WDP) areas of Kerala, the southernmost state of India The integrated climate vulnerability approach considers vulnerability as a function of three dimensions of vulnerability: adaptive capacity, sensitivity and exposure. Based on this approach a composite index, Climate Vulnerability Index for Rainfed Farming in Tropics (CVIRFT), is developed that specifically measures the vulnerability of farmers in agriculturally dominated tropical regions. As a composite index provides only a single big picture, it is essential to know if the three observed watersheds are significantly different in terms of their index value. For the assessment of robustness of the CVIRFT, a bootstrap sampling and a leave-one-out sensitivity analysis is carried out. The perceptions of farmers play a key role in determining the choices of adaptation strategies and thus the adoption process. To find out the determinants of the small holder’s adaptation strategies, a binary logistic regression model is used. The primary data used for the study was collected through 215 household surveys, 6 focus group discussions and 6 key informant interviews split among the three watershed areas. The CVIRFT comprises of three dimensions of vulnerability and the dimensions are described by 10 major components, consisting of 59 individual indicators. The watersheds show small variation in the CVIRFT values when compared. Among them, the watershed area with a WDP organized by the State Government (SG) is comparatively the least vulnerable followed by the one where a Non-Governmental Organisation (NGO) is heading the WDP. The highest vulnerability is found in the watershed where a Local self Government (LG) is leading the WDP implementation. The sensitivity analysis of CVIRFT revealed that there is no significant difference in the adaptive capacity between the three watersheds while there are significant differences in the sensitivity and the exposure dimensions. Furthermore, the sensitivity analysis of the index shows that ‘Livelihood Strategies’ and ‘Social Network’ are the most influencing major components of vulnerability. The perception study reveals that a vast majority of the households in the three study areas perceived a medium to high level of rise in average temperature and an increase in hot months. In addition, it is evident that an increase in rainfall is recognized by more than 98% of the survey participants over the three regions. However, farmers differ considerably in terms of the quantity and the selection of adaptation strategies to cope with perceived climate change. The binary logistic model depicts that various determining factors significantly affect the adaptation strategies, as for example, farming experience, male-headed households, women’s participation, education, farm size and livestock. The services rendered by the WDPs are not sufficient for an effective adaptation process by the smallholders and restructuring in sectoral wise plans and interventions is needed. The climate vulnerability assessment study is the first of its kind at watershed level, with emphasis on socio-economic factors. The composite index is replicable to further climate vulnerability assessment context, with refinement of indicators based on the locality and the targeted group. Thus, CVIRFT is a meaningful tool to develop watershed interventions and climate change adaptation strategies with a strong consideration of socio-economic characteristics

Development of a Genetic Fuzzy Controller and Its Application to a Noisy Inverted Double Pendulum

Fuzzy logic is used in a variety of applications due to its universal approximator attribute and non-linear characteristics. The tuning of the parameters of a fuzzy logic system, viz. the membership functions and the rulebase, requires a lot of trial and error. This process could be simplified by using a heuristic search algorithm like genetic algorithm (GA). In this chapter, we discuss the design of such a genetic fuzzy controller that can control an inverted double pendulum. GA improves the fuzzy logic controller (FLC) with each generation during the training process to obtain an FLC that can bring the pendulum to its inverted position. After training, the effectiveness of the FLC is tested for different scenarios by varying the initial conditions. We also show the effectiveness of the FLC even when subjected to noise and how the performance improves when the controller is tuned with noise

A CROSS-SECTIONAL STUDY ON SODIUM VALPROATE, CARBAMAZEPINE, AND LEVETIRACETAM INDUCING ENURESIS IN EPILEPTIC CHILDREN

Objectives: Enuresis or bedwetting is considered to be an underreported ADR of antiepileptic drugs (AEDs). This study assesses the incidence and comparative rate of occurrence of enuresis in children with epilepsy who are on AEDs treatment such as sodium valproate (SV); carbamazepine and levetiracetam (LEV). Methods: The study was conducted with a sample size of 32 patients. Both inpatients and outpatients between the age group >5–18 years of age previously diagnosed with epilepsy that is on monotherapy and polytherapy with SV or carbamazepine or LEV were included in the study. Patients with urinary complications or urogenital abnormalities past 3 months before admission were excluded from the study. Assessment of enuresis was done based on a questionnaire prepared from NICE guidelines and analyzed using SPSS software version 20. Results: Of 44 patients who were included in the study, only 34 came for review. Analysis of the questionnaire showed the occurrence of enuresis in 12 patients. Drugs prescribed versus assessment questions showed potent significance with eight questions; hence the hypothesis that the prescribed drugs can cause enuresis can be taken into consideration. The rate of occurrence of enuresis was analyzed in all the drugs with their respective doses, but the significant values were found only for SV 200 mg. Conclusion: This study shows the possibility of enuresis in LEV and SV treatment with a significant difference in SV. Furthermore, it showed a relation between the duration of treatment and the occurrence of enuresis

A highly accurate and scalable approach for addressing location uncertainty in asset tracking applications

Tracking systems that use RFID are increasingly being used for monitoring the movement of goods in supply chains. While these systems are effective, they still have to overcome significant challenges, such as missing reads, to improve their performance further. In this paper, we describe an optimised tracking algorithm to predict the locations of objects in the presence of missed reads using particle filters. To achieve high location accuracy we develop a model that characterises the motion of objects in a supply chain. The model is also adaptable to the changing nature of a business such as flow of goods, path taken by goods through the supply chain, and sales volumes. A scalable tracking algorithm is achieved by an object compression technique, which also leads to a significant improvement in accuracy. The results of a detailed simulation study shows that our object compression technique yields high location accuracy (above 98% at 0.95 read rate) with significant reductions in execution time and memory usage.Rengamathi Sankarkumar, Damith C. Ranasinghe, Thuraiappah Sathya

Comparison Between Genetic Fuzzy Methodology and Q-Learning for Collaborative Control Design

A comparison between two machine learning approaches viz., Genetic Fuzzy Methodology and Q-learning, is presented in this paper. The approaches are used to model controllers for a set of collaborative robots that need to work together to bring an object to a target position. The robots are fixed and are attached to the object through elastic cables. A major constraint considered in this problem is that the robots cannot communicate with each other. This means that at any instant, each robot has no motion or control information of the other robots and it can only pull or release its cable based only on the motion states of the object. This decentralized control problem provides a good example to test the capabilities and restrictions of these two machine learning approaches. The system is first trained using a set of training scenarios and then applied to an extensive test set to check the generalization achieved by each method

Evaluation of serum ferritin as a prognostic marker in acute ischemic stroke: a prospective observational study

Background: Stroke is an important health problem causing of morbidity and mortality globally. Serum ferritin has gained clinical significance as a prognostic factor that can aggravate the cytotoxicity of brain ischemia. The present study investigated the prognostic significance of serum ferritin levels with the severity of stroke using NIHSS scale.Methods: It was a prospective observational study conducted on 60 patients with acute ischemic stroke admitted in the general medicine department of a tertiary care teaching hospital. Serum ferritin levels were assessed on all participants using the instrument “immulite”. National institute of health stroke scale scoring was applied at the time of admission and on the seventh day to assess the impairment caused by a stroke. IBM SPSS version 22 was used for statistical analysis.Results: The mean serum ferritin levels at admission in patients with severe stroke, moderate stroke and mild and less stroke were 337.41±58.76, 285.56±49.37, and 197.91±111.01 ng/mL, respectively. The mean serum ferritin levels at admission were 178.76±114.70 ng/mL and 341.91±62.292 ng/mL in subjects who did not deteriorate and those who deteriorated, respectively. Whereas the mean serum ferritin levels on the sixth day were 198.34±106.88 and 348.10±57.34 ng/mL in subjects who did not deteriorate and those who deteriorated, respectively.Conclusions: Serum ferritin has a significant positive correlation with the severity of acute ischemic stroke severity on admission (p<0.001) and negative correlation with the severity of acute ischemic stroke severity on seventh day of admission (p<0.001). Thus, serum ferritin can be used as a prognostic marker in acute ischemic stroke