139 research outputs found
An analytical study of the sea water slime with reference to bacterial flora
A detailed study of the primary film of slime with reference to the bacterial flora, its quality and quantity, as observed on different material surfaces exposed to sea water is carried out. A correlation has been established between bacteria and slime deposited on different surfaces
Effect of sulphide on corrosion of copper in seawater
The corrosion of ETP copper in natural seawater and putrid seawater has been studied. The corrosion rates and the sulphide content were monitored at regular intervals. In the absence of oxygen in the putrid media, the presence of sulphide favoured a reduction in the corrosion rate
Designing of a single pack wash primer for aluminium surfaces in a marine environment
Design aspects and comparative performances of different laboratory formulations of wash primers were studied under laboratory and field conditions with reference to scratch hardness, flexibility, stability, resistance to corrosion and adhesiveness. The different formulations of single pack wash primers tested have shown superiority of the formulation prepared out of “mowital” and that it is comparable in performance to double pack wash primer
Hydrography of the Cochin harbour
The hydrography of the Cochin harbour is studied with reference to air temperature, dissolved oxygen, salinity and pH. The analysis of the data shows unique hydrographical characteristics which are influenced by the monsoon rains. The uniqueness lies mainly in the fluctuations of salinity which registers as low as 0.6‰ during monsoon period to near sea conditions (29.4‰) during the summer period. The dissolved oxygen, temperature and pH also showed fluctuations corresponding to seasons
On the development of a mercury-free ternary aluminium anode for cathodic protection
The development of a new mercury-free ternary aluminum anode (CIFTAL) for cathodic protection of marine structures is described. The new anode demonstrated a current efficiency of 83.5% to 85.4% in a current density range of 5.6 to 166.7 mAdmˉ². The current efficiency remained practically stable at 1.4 mAdmˉ² over a test period of 300 days. The service trials of the anode on steel trawlers and aluminum (Indal M 57 S) sheathed wooden boats have shown satisfactory performance in terms of uniform dissolution, current efficiency and driving voltage. In the wake of legislations restricting the use of anodes containing mercury in an endeavor to control the mercury pollution of the near shore aquatic environment, the new anode (CIFTAL) with its stable current output and high current efficiency merits significance in marine cathodic protection
Selection of materials for marine instruments
The paper describes the selection of materials for the reliable operation of oceanographic instruments. For selecting the material, raft immersion tests were carried out for one year. Results of the tests are presented. Comparisons between metals were discussed
Experimental formulation of an anti fouling paint with tributyl tin oxide as toxic pigment
Results of the experimental formulation of an antifouling paint incorporating TBTO as toxic pigment are presented in this paper. Of the various resins tested, namely, phenolic, cashew nut shell liquid (CNSL), epoxy linseed oil with rosin and limed rosin, the paint composition with limed rosin gave the critical leaching rate of TBTO. Acid alkali test showed dissolution of matrix and visible migration of toxin to the surface. Accelerated corrosion tests had not recorded any signs of corrosion in panels painted with or without barrier coat. Raft exposure studies indicated that the new formulation could resist fouling accumulation on painted panels for 9 months
Soft Computing for Robust Secure Wireless Reception
Soft computing is a collection of different computing methodologies that include neuro computing, fuzzy logic, evolutionary computing, and probabilistic reasoning. These are aimed to exploit the tolerance for imprecision and uncertainty to achieve tractability, robustness, and low solution cost. This paper presents a brief overview of soft computing components, followed by typical realization, via simulation of a wireless receiver employing a hybrid soft computing technique to illustrate its application in a fading signal propagation scenario.Defence Science Journal, 2009, 59(5), pp.517-523, DOI:http://dx.doi.org/10.14429/dsj.59.155
Could plasma zinc be a predictor for mortality and severity in sepsis syndrome?
Background: While many factors are known to play a role in outcomes of sepsis, the role of micronutrients such as zinc remains a gray area. This study assesses the correlation of plasma zinc levels with mortality and severity of sepsis. Objective was to study the association between plasma zinc levels with mortality and severity of sepsis.Methods: Comparative prospective observational study which included 89 patients with proven sepsis according to the society of critical care medicine (SCCM) guidelines. The study was conducted at a tertiary care centre in South India. A total of 89 patients who were admitted into the medical ICU directly from ER, from December 2014 to August 2015 were chosen for the study after satisfying specific inclusion criteria and divided into 2 outcome groups based on mortality.Results: There was a significant association between plasma zinc (categorized as low, normal and high plasma zinc) and outcome. While the severity of sepsis as per SOFA score on admission did not have an association, there was a significant association between plasma zinc and the 48-hour SOFA score.Conclusions: Higher plasma zinc values had lower mortality and lower 48 hours SOFA score, strengthening the hypothesis regarding the role of zinc in the immune response to sepsis. More research is needed regarding the role of zinc in assessing the severity and predicting the mortality of patients with sepsis
Expressions of psychological stress on Twitter: detection and characterisation
A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.Long-term psychological stress is a significant predictive factor for individual mental health and short-term stress is a useful indicator of an immediate problem. Traditional psychology studies have relied on surveys to understand reasons for stress in general and in specific contexts. The popularity and ubiquity of social media make it a potential data source for identifying and characterising aspects of stress. Previous studies of stress in social media have focused on users responding to stressful personal life events. Prior social media research has not explored expressions of stress in other important domains, however, including travel and politics.
This thesis detects and analyses expressions of psychological stress in social media. So far, TensiStrength is the only existing lexicon for stress and relaxation scores in social media. Using a word-vector based word sense disambiguation method, the TensiStrength lexicon was modified to include the stress scores of the different senses of the same word. On a dataset of 1000 tweets containing ambiguous stress-related words, the accuracy of the modified TensiStrength increased by 4.3%.
This thesis also finds and reports characteristics of a multiple-domain stress dataset of 12000 tweets, 3000 each for airlines, personal events, UK politics, and London traffic. A two-step method for identifying stressors in tweets was implemented. The first step used LDA topic modelling and k-means clustering to find a set of types of stressors (e.g., delay, accident). Second, three word-vector based methods - maximum-word similarity, context-vector similarity, and cluster-vector similarity - were used to detect the stressors in each tweet. The cluster vector similarity method was found to identify the stressors in tweets in all four domains better than machine learning classifiers, based on the performance metrics of accuracy, precision, recall, and f-measure.
Swearing and sarcasm were also analysed in high-stress and no-stress datasets from the four domains using a Convolutional Neural Network and Multilayer Perceptron, respectively. The presence of swearing and sarcasm was higher in the high-stress tweets compared to no-stress tweets in all the domains. The stressors in each domain with higher percentages of swearing or sarcasm were identified. Furthermore, the distribution of the temporal classes (past, present, future, and atemporal) in high-stress tweets was found using an ensemble classifier. The distribution depended on the domain and the stressors.
This study contributes a modified and improved lexicon for the identification of stress scores in social media texts. The two-step method to identify stressors follows a general framework that can be used for domains other than those which were studied. The presence of swearing, sarcasm, and the temporal classes of high-stress tweets belonging to different domains are found and compared to the findings from traditional psychology, for the first time. The algorithms and knowledge may be useful for travel, political, and personal life systems that need to identify stressful events in order to take appropriate action.European Union's Horizon 2020 research and innovation programme under grant agreement No 636160-2, the Optimum project (www.optimumproject.eu)
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