Articulating the Art: An Appraisal of the Emerging Trend of Graphic Novels in the Contemporary Indian English Writing in reference to Amruta Patil’s Works

In olden days, the art of storytelling in the Indian sub-continent was expressed through spoken words. The significant facet of story narration involved some visual experiences that engaged the listeners both literate and illiterate enjoy and explore their own history, tradition and culture of India as they heed to Indian stories like Mahabharata, Ramayana and other texts. However, the dawn of written texts gradually made the traditional storytelling insignificant and favored only the educated. There are crowds who prefer watching adapted movies than books. Neither the adapted movies give major insights of the story of the book nor are all good books adapted. Regardless, the growth of the graphic novels began to grasp the attention of mass population including the illiterate as well as children who are reluctant to read. Graphic novels also help non readers understand the story through the captivating images of the story if words are hard. The essence of Indian Graphic novels is the visibility of Indian life, culture, tradition and customs through pictures thereby making the subject clear and percipient. In recent time, the Indian author Amruta Patil made her wide contribution to the growth of Indian Graphic Novels. She is also the first female graphic novelist. This paper aims to recognize her works towards the development of Indian Graphic Novels and also her prudent attention to the themes of her works which touches upon gender politics, social issues, ecological awareness and recreating mythology for contemporary readers. This paper explores all her works that include Kari, Adiparva: Churning of the Ocean, Sauptik: Blood and Flowers and Aranyaka: Book of the Forest. Being a professional visual artist, the subject of her works is strongly portrayed through her illustration incorporated with acrylic painting, collage, watercolor and Charcoal. Her works are indeed a major initiation to the growth of Indian graphic novels

Low-Complexity Detection/Equalization in Large-Dimension MIMO-ISI Channels Using Graphical Models

In this paper, we deal with low-complexity near-optimal detection/equalization in large-dimension multiple-input multiple-output inter-symbol interference (MIMO-ISI) channels using message passing on graphical models. A key contribution in the paper is the demonstration that near-optimal performance in MIMO-ISI channels with large dimensions can be achieved at low complexities through simple yet effective simplifications/approximations, although the graphical models that represent MIMO-ISI channels are fully/densely connected (loopy graphs). These include 1) use of Markov Random Field (MRF) based graphical model with pairwise interaction, in conjunction with {\em message/belief damping}, and 2) use of Factor Graph (FG) based graphical model with {\em Gaussian approximation of interference} (GAI). The per-symbol complexities are $O(K^2n_t^2)$ and $O(Kn_t)$ for the MRF and the FG with GAI approaches, respectively, where $K$ and $n_t$ denote the number of channel uses per frame, and number of transmit antennas, respectively. These low-complexities are quite attractive for large dimensions, i.e., for large $Kn_t$. From a performance perspective, these algorithms are even more interesting in large-dimensions since they achieve increasingly closer to optimum detection performance for increasing $Kn_t$. Also, we show that these message passing algorithms can be used in an iterative manner with local neighborhood search algorithms to improve the reliability/performance of $M$-QAM symbol detection

Influence of Moisture Content and Oxygen Concentration on Biodegradation of Petroleum Hydrocarbons

The biodegradability of petroleum hydrocarbons was evaluated using petroleum oily sludge from VRL logistics ltd situated at Kengeri, Bangalore (India). The soil rich in native microorganisms was collected from Bangalore University campus and the same is used to prepare simulated contaminated soil. The initial Total petroleum hydrocarbons (TPH) concentration in the simulated contaminated soil was 83,940 mg /kg of soil. Biodegradation was examined for three different conditions i.e. four bioreactors for studying variation of moisture, four bioreactors for studying variation of oxygen and one bioreactor as control Treatability studies on TPH contaminated soil was conducted for 12 weeks to evaluate TPH mass loss rates under the most favorable conditions, for which a set of nine bioreactors each with 15 kg of fresh soil, 3 kgs of oily sludge, 1.5 kgs of inoculated soil in the ratio of (10:2:1) were thoroughly mixed and maintained under laboratory conditions. The TPH, moisture content, pH, bacterial counts and oxygen were monitored regularly along with the nutrient concentration i.e.. C: N: P ratio maintained at 100:10:1 in all the bioreactors except the control reactor. From the study it is concluded that the optimal conditions for better degradation of TPH is found to be between 50% - 60% of moisture content with biodegradation rate of 0.0128 - 0.0174 day1 and TPH removal efficiency of 68.5 - 79.2% and oxygen concentration of 50 - 60 mg/kg/day, with biodegradation rate of 0.012

A Pilot study to look at the effect of IL-28B polymorphism on IL-28 expression and immunological recovery among HIV-1 infected individuals following Antiretroviral Therapy

OBJECTIVES: To look at the frequency of IL-28B polymorphisms in south Indian HIV infected individuals and its effect on IL-28 plasma level and immunological recovery following ART. METHODS: A total of 49 HIV infected individuals and 30 healthy controls were recruited. Whole blood samples were collected before and after 6-9 months of ART from patients. Absolute CD4+/CD8+ T cell counts, CD3+cell counts and CD4/CD8 ratio were estimated using flow cytometry (FACS Count). IL-28B polymorphism at rs12979860 and rs8099917 were detected by PCR-RFLP and IL-28B plasma level estimation was done by ELISA. Association between polymorphism, cell counts and IL-28 plasma level were analyzed. RESULTS: There was significant association of CC genotype at rs12979860 (p=0.03) and CC/TT haplotype (p=0.03) with higher CD4+T-cell count among treatment naïve HIV infected individuals. There was a significant (p=0.03) association of CC/TT haplotype with increase in CD4/CD3% following ART. There was no correlation (p=>0.05) between IL-28B plasma level with IL-28B polymorphism, CD4+ T cell and CD4/CD8 ratio. There was no significant difference in the frequency of polymorphism and IL-28B plasma level between HIV infected individuals and healthy controls. The CT/GT haplotype had a significant higher IL-28B plasma level compared to wild type CC/TT before the initiation of ART and significantly higher decrease observed in CT/GT haplotype compared to CC/TT wild type were significant. CONCLUSION: In conclusion our preliminary data from this pilot study showed significantly higher CD4+ Tcells among HIV infected individuals with wild haplotype (CC/TT) prior to ART and significantly high CD4+ T cells and CD4/CD3% following ART. This study showed no association of IL-28B polymorphism with IL-28B plasma level and CD4+T cell count or CD4/CD8 ratio. Since IFNλ is a powerful immune modulator functional studies are warranted to understand the IFNλ mediated immuno-pathogeneis in HIV infection

Early and Accurate Prediction of Heart Disease Using Machine Learning Model

Heart disease is one of the critical health issues and many people across the world are suffering with this disease. It is important to identify this disease in early stages to save many lives. The purpose of this article is to design a model to predict the heart diseases using machine learning techniques. This model is developed using classification algorithms, as they play important role in prediction. The model is developed using different classification algorithms which include Logistic Regression, Random Forest, Support vector machine, Gaussian Naïve Bayes, Gradient boosting, K-nearest neighbours, Multinomial Naïve bayes and Decision trees. Cleveland data repository is used to train and test the classifiers. In addition to this, feature selection algorithm named chi square is used to select key features from the input data set, which will decrease the execution time and increases the performance of the classifiers. Out of all the classifiers evaluated using performance metrics, Random forest is giving good accuracy. So, the model built using Random forest is efficient and feasible solution in identifying heart diseases and it can be implemented in healthcare which plays key role in the stream of cardiology. &nbsp

Demarcation of Ground Water Potential Zones using Remote Sensing and GIS Applications

Now-a-days, due to the high demand of water for the human needs, groundwater sources are drastically extracted and causing to least the source. The entire Yearly furnish is contributing from the utmost resource called Groundwater. Globally, groundwater is extracting primarily for the purpose of agricultural fields, domestic and for industrial water supply. Majority of the surface water is in the form of saline water which is not useful for the needs of human beings for their daily needs. Very less amount of fresh surface water is existing on the ground surface. To compensate the needs, it is essential to identify, extract and manage the groundwater which is available at different levels at different areas of the globe. Proper planning is required for the extraction of groundwater using updated technologies for using and maintaining of natural resources like water resources. The prime strive of the selected project area is to map out potential groundwater regions in the Pendlimarri Mandal of Kadapa District by using Geospatial Technology. The main impartial target of the work is to select appropriate methods and assessment criteria of the technology to identify the potential underground demarcations in geographic information system environment with help of ArcGIS software. To demarcate zones of groundwater potential, various key parameters called geology, lineament density, LU / LC, geomorphology, groundwater depths, slope and drainage pattern were prepared by utilizing remote sensing data and secondary data which can collect from concern departments. The thematic layers are to be finally integrated by using weighted overlay analysis of spatial analyst tools of data management tools of ArcMap software to delineate underground water prospects regions output layout of the project. Disparate groundwater prospects levels were categorized, from the range excellent to poor including very good, good and moderate in between. At last, decided that that the applications of geoinformatics are essential and effectively applied for the demarcation of potential zones of groundwater

IMPACT OF BIG DATA AND EMERGING RESEARCH TRENDS

The term big data is extensively used in many computational and decision making domains. Big data is nothing but the large data sets formed from various sources and are almost impossible to process and analyse using traditional approaches because of its complexity. Efficient analysis and processing of big data within a given time frame is essential for it to be useful. Various technologies like Hadoop, MapReduce, etc. are used to analyse the big data and hence possible to retrieve knowledge from the large datasets. This paper focuses on the impact of big data, the technologies in big data processing and its limitations and the emerging trends in big data

Female Audit Partners and Extended Audit Reporting: UK Evidence

This study investigates whether audit partner gender is associated with the extent of auditor disclosure and the communication style regarding risks of material misstatements that are classified as key audit matters (KAMs). Using a sample of UK firms during the 2013–2017 period, our results suggest that female audit partners are more likely than male audit partners to disclose more KAMs with more details after controlling for both client and audit firm attributes. Furthermore, female audit partners are found to use a less optimistic tone and provide less readable audit reports, compared to their male counterparts, suggesting that behavioural variances between female and male audit partners may have significant implications on their writing style. Therefore, this study offers new insights on the role of audit partner gender in extended audit reporting. Our findings have important implications for audit firms, investors, policymakers and governments in relation to the development, implementation and enforcement of gender diversity