A Study on The Awareness of Consanguinity & Various Genetic Aspects Among the Parents of Children with Beta Thalassemia and To Understand the Usefulness of Various Indices in Identifying Beta Thalassemia Carriers in A Cohort of South Indian Patients

Background: Beta thalassemia is one of the common single gene disorders in India. Screening relies on High performance Liquid Chromatography (HPLC) / Hemoglobin electrophoresis. But this being an expensive test, we looked at the usefulness of red blood cell indices in the identification of beta thalassemia carriers. We have also looked at the proportion of consanguinity and the awareness of genetic aspects of Beta thalassemia in this cohort. Methods: This is an observational study among parents of children with Beta thalassemia major attending hematology out-patient Department in a tertiary care centre in Chennai, South India. Their complete hemograms were analysed using Mentzer Index, Srivastava Index and Green & King Index. They were also asked to fill in a questionnaire to understand their level of awareness of Beta thalassemia, consanguinity and other demographic parameters. Results: Though the three indices were able to identify majority of the carriers, they missed 10-20% of carriers underscoring the fact that Complete Blood counts and HPLC together would remain the best modality.53% of this cohort were graduates and 26.7% were consanguineous. None of the parents had heard of thalassemia before their child’s diagnosis.53.3% understood the genetic nature of this disorder. Conclusion: Evaluating complete hemogram and HPLC would be the ideal screening method to identify Beta thalassemia carriers. More awareness needs to be initiated in the community about Beta thalassemia and universal screening for Beta thalassemia in all adults >18 years or at least for antenatal mothers should be initiated at the earliest

Awareness Of Beta -Thalassemia In Tamil Nadu, India: Llustrated By 2 Case Scenarios: Urgent Need For Increasing Awareness

Background: Beta thalassemia is an autosomal recessive inherited genetic disorder which is emerging as an important disease with a huge economic burden on India. Health policy makers need to recognize this and plan strategies for effective awareness and prevention programs throughout the country and not just the tribal areas. Case report: We present two families with more than one child with beta thalassemia major and discuss the factors regarding the recurrence. In the first family, both children were siblings while in the second family they were cousins. Results:  Both the families were not aware of the existence of thalassemia before the diagnosis in their children in the first family. The delay in diagnosis was due to the late presentation of the disease. In the second family there was a lack of awareness of the genetic nature of the disease which prevented the family from seeking preventive measures. Conclusion: Awareness about beta thalassemia and the screening facilities available should be popularized by policy makers so that people are empowered to use them without any stigmatization or discrimination. &nbsp

Significant Feature Selection Method for Health Domain using Computational Intelligence- A Case Study for Heart Disease

In the medical field, the diagnosing of cardiovascular disease is that the most troublesome task. The diagnosis of heart disease is difficult as a decision relied on grouping of large clinical and pathological data. Due to this complication, the interest increased in a very vital quantity between the researchers and clinical professionals regarding the economical and correct heart disease prediction. In case of heart disease, the correct diagnosis in early stage is important as time is the very important factor. Heart disease is the principal supply of deaths widespread, and the prediction of Heart Disease is significant at an untimely phase. Machine learning in recent years has been the evolving, reliable and supporting tools in medical domain and has provided the best support for predicting disease with correct case of training and testing. The main idea behind this work is to find relevant heart disease feature among the large number of feature using rough computational Intelligence approach. The proposed feature selection approach performance is better than traditional feature selection approaches. The performances of the rough computation approach is tested with different heart disease data sets and validated with real-time data sets

Development of an automated physician review classification system: A novel semi-supervised learning approach

Building automated text classifiers have assumed significant importance since the development of large online information platforms. Several compelling use cases have emerged in the field of artificial intelligence and analytics in recent years. However, building and training text classifiers become problematic in the healthcare context, which deals with a sensitive and limited volume of data. In this paper, we explore the development of a classifier and apply it to a specific case of classifying physician reviews into either clinical and non-clinical reviews. The primary purpose of this paper is to demonstrate the methodology using which the classifier has been developed, including a novel technique in curating datasets. We leverage unsupervised guided Latent Dirichlet Allocation (LDA) method and supervised methods such as deep neural networks, Long-Short Term Memory (LSTM) networks, and Bi-directional LSTMs. Further, we compare the various models and choose the one with the best classification performance by validating the output results with the ground truth. Our methodology provides insights into making the best use of semi-supervised and supervised algorithms along with grounded data for developing classifiers that can be generalized for other novel contexts where dataset availability is limited

Health management design considerations for an all electric aircraft

This paper explains the On-board IVHM system for a State-Of-the-Art “All electric aircraft” and explores implementing practices for analysis based design, illustrations and development of IVHM capabilities. On implementing the system as an on board system will carry out fault detection and isolation, recommend maintenance action, provides prognostic capabilities to highest possible problems before these became critical. The vehicle Condition Based Maintenance (CBM) and adaptive control algorithm development based on an open architecture system which allow “Plug in and Plug off” various systems in a more efficient and flexible way. The scope of the IVHM design included consideration of data collection and communication from the continuous monitoring of aircraft systems, observation of current system states, and processing of this data to support proper maintenance and repair actions. Legacy commercial platforms and HM applications for various subsystems of these aircraft were identified. The list of possible applications was down-selected to a reduced number that offer the highest value using a QFD matrix based on the cost benefit analysis. Requirements, designs and system architectures were developed for these applications. The application areas considered included engine, tires and brakes, pneumatics and air conditioning, generator, and structures. IVHM design program included identification of application sensors, functions and interfaces; IVHM system architecture, descriptions of certification requirements and approaches; the results of a cost/benefit analyses and recommended standards and technology gaps. The work concluded with observations on nature of HM, the technologies, and the approaches and challenges to its integration into the current avionics, support system and business infrastructure. The IVHM design for All Electric Hybrid Wing Body (HWB) Aircraft has a challenging task of addressing and resolving the shortfalls in the legacy IVHM framework. The challenges like sensor battery maintenance, handling big data from SHM, On-Ground Data transfer by light, Extraction of required features at sensor nodes/RDCUs, ECAM/EICAS Interfaces, issues of certification of wireless SHM network has been addressed in this paper. Automatic Deployable Flight Data recorders are used in the design of HWB aircraft in which critical flight parameters are recorded. The component selection of IVHM system including software and hardware have been based on the COTS technology. The design emphasis on high levels of reliability and maintainability. The above systems are employed using IMA and integrated on AFDX data bus. The design activities has to pass through design reviews on systematic basis and the overall approach has been to make system highly lighter, effective “All weather” compatible and modular. It is concluded from the study of advancement in IVHM capabilities and new service offerings that IVHM technology is emerging as well as challenging. With the inclusion of adaptive control, vehicle condition based maintenance and pilot fatigue monitoring, IVHM evolved as a more proactively involved on-board system

Development of an Automated Physician Review Classification System: A hybrid Machine Learning Approach

Patients are increasingly turning to physician rating websites to help them make important healthcare decisions, such as selecting primary care doctors, specialists, and supplementary medical care providers. Previous research has identified a variety of topics and themes that emerge on these review platforms. However, there is little or no work that has been done to create an automated classifier that automatically categorizes these reviews into distinct topics after they have been explored in this context. Building such an automated classifier could assist IS developers and other stakeholders in automatically classifying patient reviews and understanding patient needs. Furthermore, using design science research we strategize how such machine learning systems can be built using design guidelines in turn having the potential to be generalized to other specific contextual problem spaces. Our work focuses on laying the foundation to design guidelines that need to be followed while building automated systems in specific contexts

A TOGAF Based Chatbot Evaluation Metrics: Insights from Literature Review

Chatbots have been used for basic conversational functionalities and task performance in today\u27s world. With the surge in the use of chatbots, several design features have emerged to cater to its rising demands and increasing complexity. Researchers have grappled with the issues of modeling and evaluating these tools because of the vast number of metrics associated with their measure of successful. This paper conducted a literature survey to identify the various conversational metrics used to evaluate chatbots. The selected evaluation metrics were mapped to the various layers of The Open Group Architecture Framework (TOGAF) architecture. TOGAF architecture helped us divide the metrics based on the various facets critical to developing successful chatbot applications. Our results show that the metrics related to the business layer have been well studied. However, metrics associated with the data, information, and system layers warrant more research. As chatbots become more complex, success metrics across the intermediate layers may assume greater significance

Opinion mining in Machine Learning for High Perfomance using Sentimental Analysis

Opinion mining refers to the use of the natural language processing in which it is used for linguistics to identify and extract information .Opinion mining has been an indispensible part of present scenario. Due to large amount of online app development and processing of all data through internet Opinion has become one of the major part in reviewing through online. A various kinds of probabilistic topic modeling technique are available to analyze and extract the idea behind the probability distribution over words. In proposed review system, a review of a particular product that brought in is Amazon, opinion review dataset of a particular product by UPC database and it is pre-processed to give a result by machine learning to get specific opinion word using sentimental analyses. LDA model is applied into the machine learning technique to analyses. It also determine the large amount of time required for determining the opinion of a particular product that is purchased. Experimental evaluation shows that our proposed techniques are efficient and perform better than previously proposed technique, however, the proposed technique can be used by any other languages

Aerodynamics And Performance Of Variable Pitch Vertical Axis Turbines At Low Tip Speed Ratios

The shift to renewable energy is imminent to aid the reduce its total carbon footprint and fight off global warming. Wind and hydrokinetic energy have great potential to replace the depleting reserves of fossil fuels. With its scalability and omnidirectional advantage, vertical-axis turbines are a great renewable energy source for off-grid and rural areas. Although the vertical characteristics of the turbine look promising, it is known to have far lower performance than its horizontal counterpart. This research investigates the detailed aerodynamic study of lift and drag contribution on the turbine blades with variablepitch blade through numerical simulation via an open-source software called Qblade. The problems to be investigated in this research are the effects of pitch angle on the aerodynamic contribution of the blades and the variable-pitch model to improve performance over various operating ranges. It is suggested that applying pitch angle to the blade at a controlled amount can help maintain a constant steady angle of attack, which can be altered to extract the most performance. The effects of blade pitching would be studied to determine the instantaneous aerodynamic loadings, the tangential and normal forces while ultimately referencing the average power coefficient, for overall performance. Variable-pitch blade will be employed in this study to compare and determine the benefit and drawback of the pitching method for vertical-axis turbine performance. The investigation would be carried out by a series of numerical simulations of a single-bladed Darrieus turbine in Qblade using the Lifting Line Free Vortex Wake (LLT) module. A single blade is chosen to solely study the complete aerodynamic loading without compromising the effects of multiple blades and complex wakes. The blade Blade Designer module with a NACA 0018 airfoil profile and experimentally tested extrapolated airfoil polar data to ensure realistic and accurate data. Validation studies are then carried out by comparing the simulated results from Qblade to Computational Fluid Dynamics (CFD) solution and experimental tests to ensure the method and model used in the simulation are accurate and trustworthy. The data obtained from Qblade is then processed in MATLAB to observe the aerodynamic loads on the blade and the aerodynamic contribution to the power produced in a turbine rotation. A fine-tuned variable-pitch blade will be created through MATLAB and implemented via Simulation Input Files in a turbine model in Qblade. LLT simulation would be carried out for low tip-speed ratios of 0.75, 1.0, 1.6, 2.0, and 2.5, allowing us to observe the impact of different tip-speed ratios on variable-pitch blade

Occurrence of phthirapteran ectoparasite parasitizing on domestic dogs, Canis familiaris (Linne) in Jaunpur district (U.P.)

Only two species of biting louse, Heterodoxus spiniger (Enderlein) (43.27%) and Trichodectes canis (De Geer) (13.47%) have been recorded from 245 dogs examined in twelve different localities in Jaunpur district during 2009 to 2011. Female dogs were found most prevalent in comparison to the male in both the cases. Different parameters like host sex, hair colour, hygienic condition, health and age group have been taken into the consideration during the survey. Older age groups, unhealthy and unhygienic condition of dogs were found more prone for the lice. In case of relative intensity of lice 38% were found moderately infested with H. spiniger while 23% and 16% were very light and light infested. Only 12% could be recorded heavy infested dog while 8% remained very heavy infested. Similar trends were recorded for T. canis where moderate infestation followed by very light, light, heavy and very heavy infestation respectively. Besides these two lice, some other ectoparasites (ticks, mites and fleas) (5.31%) were also recorded casually but not used the data for prevalence